Meetups & Events

PostgreSQL with Apache Ignite: Faster Transactions and Analytics

New York City PostgreSQL User Group, Speaker - Akmal Chaudhri

August 30, 2018

Combining Apache Ignite with PostgreSQL can offer enterprises the best of both open-source worlds: a highly-scalable high-velocity grid-based in-memory SQL database, with a robust fully-featured SQL persistent datastore for advanced analytics and data-warehouse capabilities. Topics to be covered:

  • How to complement PostgreSQL for Hybrid Transactional/Analytical Processing (HTAP) by leveraging the massive parallel processing and SQL capabilities of Apache Ignite.
  • How to use Apache Ignite as an In-Memory Data Grid that stores data in memory and boosts applications performance by offloading reads from PostgreSQL.
  • The strategic benefits of using Apache Ignite instead of Memcache, Redis, GigaSpaces, or Oracle Coherence.

 

Machine and Deep Learning with an Apache Ignite

NYC In-Memory Computing Meetup, Speaker - Akmal Chaudhri

August 29, 2018

Apache Ignite Release 2.4 added built-in machine learning (ML) and deep learning (DL). It not only eliminates any delays caused by transferring data to a different database or store. It delivers near real-time performance by running a variety of ML and DL algorithms in place, in memory, that are optimized for collocated processing.

Learn more about these new capabilities and how to use them in Apache Ignite 2.4. In his talk, Akmal will provide:

  • An overview of the ML and DL algorithms and how they work
  • Examples of how to implement each ML and DL algorithm
  • Tips and tricks for getting the most performance out of ML and DL

 

Improving Apache Spark™ In-Memory Computing with Apache Ignite™

Big Bang Data Science - Georgia, Speaker - Akmal Chaudhri

August 28, 2018

Learn how Apache Ignite simplifies development and improves performance for Apache Spark. In his talk, Akmal Chaudhri will explain how Apache Spark and Ignite are integrated, and how they are used together for analytics, stream processing and machine learning.

By the end of this talk you will understand:

  • How Apache Ignite's native RDD and new native DataFrame APIs work
  • How to use Ignite as an in-memory database and massively parallel processing (MPP) style collocated processing for preparing and managing data for Spark
  • How to leverage Ignite to easily share state across Spark jobs using mutable RDDs and DataFrames
  • How to leverage Ignite distributed SQL and advanced indexing in memory to improve SQL performance

 

Speeding-up the IoT: Best practices for stream ingestion, processing and analytics using in-memory computing

Greater Atlanta Internet of Things, Speaker - Akmal Chaudhri

August 27, 2018

In this talk, Akmal Chaudhri will share the best practices used for real-time stream ingestion, processing and analytics using Apache Ignite, Apache Kafka, Apache Spark and other technologies. Akmal will explain how to:

  • Optimize stream ingestion from Kafka and other popular messaging and streaming technologies
  • Architect pre-processing and analytics for performance and scalability
  • Implement and tune Apache Ignite and Spark together
  • Design to ensure performance for real-time reports

 

Best Practices for Deploying Distributed Databases and In-Memory Computing Platforms with Kubernetes

Bay Area In-Memory Computing Meetup, Menlo Park, Speaker - Denis Magda

August 23, 2018

Denis will explain how Kubernetes can orchestrate a distributed database or in-memory computing solutions using Apache Ignite as an example. He'll demonstrate how to:

  • Deploy, provision and manage an IMDG or IMDB when you wish to keep data in RAM
  • Set up and manage persistence for the in-memory technologies above or configure a disk-based distributed database
  • Set up auto-discovery and automated horizontal scalability, and use other tricks for high availability

 

Apache Ignite + Apache Spark RDDs and DataFrames integration (ENG)

Data Summer Conf, Ukraine, Speaker - Akmal Chaudhri

July 21, 2018

This session will explain how Apache Spark and Ignite are integrated, and how they are used to together for analytics, stream processing and machine learning. By the end of this session attendees will understand:

  • How Apache Ignite’s native RDD and new native DataFrame APIs work
  • How to use Ignite as an in-memory database and massively parallel processing (MPP) style collocated processing for preparing and managing data for Spark
  • How to leverage Ignite to easily share state across Spark jobs using mutable RDDs and DataFrames
  • How to leverage Ignite distributed SQL and advanced indexing in memory to improve SQL performance

 

Adding Speed and Scale to Existing Applications with No Rip and Replace Using Apache Ignite

Big Data, San Francisco v 5.0, Speaker - Denis Magda

July 18, 2018

Learn how companies are not only adding speed and scale without ripping out, rewriting or replacing their existing applications and databases, but also how they're setting themselves up for future projects to improve the customer experience. In this talk, Denis will explain how to:

  • Get started with Apache Ignite as In-Memory Data Grid (IMDG) deployed on top of RDBMS or NoSQL database
  • Keep data in sync across RAM (Apache Ignite) and disk (RDBMS/NoSQL database)
  • Leverage from Apache Ignite distributed SQL and ACID transaction for IMDG scenarios
  • Move further and start to build HTAP applications, real-time analytics, and machine learning, on the same IMDG

 

Machine and Deep Learning with in-memory computing

London In-Memory Computing Meetup, Speaker - Akmal Chaudhri

July 18, 2018

Apache Ignite is an open-source distributed database, caching and processing platform designed to store and compute on large volumes of data across a cluster of nodes. Using this free, open-source software, Akmal will give:

  • An overview of the ML and DL algorithms and how they work
  • Examples of how to implement each ML and DL algorithm
  • Tips and tricks for getting the most performance out of ML and DL

 

Best Practices for Deploying Distributed Databases and In-Memory Computing Platforms with Kubernetes

Webinar, Speaker - Denis Magda

July 11, 2018

In-memory computing technologies such as in-memory data grids (IMDG) and databases (IMDB), NoSQL and NewSQL databases can make so many things easier for a developer. But implementing DevOps for these distributed technologies and the related storage can be difficult. Luckily Kubernetes has come to the rescue!

In this webinar, learn how Kubernetes can orchestrate a distributed database or in-memory computing solutions using Apache Ignite as an example.

 

In-Memory Computing Essentials for Architects and Developers: Part 1

Webinar, Speaker - Akmal Chaudhri

July 03, 2018

In this webinar, Akmal Chaudhri will introduce the fundamental capabilities and components of an in-memory computing platform with a focus on Apache Ignite, and demonstrate how to apply the theory in practice. With increasingly advanced coding examples, architects and developers will learn about:

  • Cluster configuration and deployment
  • Data processing with key-value APIs
  • Data processing with SQL

 

Distributed Database DevOps Dilemmas? Kubernetes to the rescue!

DockerNYC, Speaker - Denis Magda

June 28, 2018

Distributed databases can make so many things easier for a developer, but not always for DevOps. Kubernetes has come to the rescue with an easy application orchestration! It is straightforward to do the orchestration leaning on relational databases as a data layer. However, it is more difficult to do the same when a distributed SQL database or other kind of distributed storage is used instead. In this presentation, attendees will learn how Kubernetes can orchestrate a distributed database like Apache Ignite, in particular:

  • Cluster Assembling - database nodes auto-discovery in Kubernetes
  • Database Resilience - automated horizontal scalability
  • Database Availability - what’s the role of Kubernetes and the database
  • Utilizing both RAM and disk - set up Apache Ignite in a way to get in-memory performance with the durability of disk

 

Scale Out and Conquer: Architectural Decisions Behind Distributed In-Memory Systems

NYC In-Memory Computing Meetup, Speaker - Denis Magda

June 27, 2018

In this talk attendees will learn about the compromises and pitfalls architects face when designing distributed systems:

  • Advantages and disadvantages of different data-sharding algorithms
  • Effective data models for distributed environments
  • Synchronization and coordination in distributed systems
  • Local scalability issues of speeding up local processing on cluster nodes

 

Apache Cassandra vs Apache Ignite for HTAP

SQL NYC Database Meetup, Speaker - Denis Magda

June 26, 2018

Join Denis Magda to learn the current best-practices for HTAP along with the differences between Apache Cassandra and Apache Ignite, two of the most-common technologies utilized for Hybrid Transactional/Analytical Processing. This session will cover:

  • A detailed comparison of Apache Ignite and Apache Cassandra for HTAP applications
  • The requirements for real-time, high volume HTAP applications
  • Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale

 

Building New Hybrid Transactional/Operational Processing (HTAP) Applications With Apache® Ignite™

Webinar, Speaker - Denis Magda

June 20, 2018

Learn how companies build new HTAP applications with in-memory computing that leverage analytics within transactions to improve business outcomes. This is how many retail innovators like Amazon, Expedia/HomeAway or SaaS innovators like Workday have succeeded. This webinar will explain with examples on how to:

  • Merge operational data and analytics together, so that analytics can work against the most recent data
  • Improve processing and analytics scalability with massively parallel processing (MPP)
  • Increase transaction throughput using a combination of distributed SQL, ACID transaction support and native persistence
  • Synchronize data and transactions with existing systems

 

Distributed Database DevOps Dilemmas? Kubernetes to the rescue!

Containerdays, Hamburg, Speaker - Akmal Chaudhri

June 19, 2018

Distributed databases can make so many things easier for a developer, but not always for DevOps. Kubernetes has come to the rescue with an easy application orchestration! It is straightforward to do the orchestration leaning on relational databases as a data layer. However, it is more difficult to do the same when a distributed SQL database or other kind of distributed storage is used instead. In this presentation, attendees will learn how Kubernetes can orchestrate a distributed database like Apache Ignite, in particular:

  • Cluster Assembling - database nodes auto-discovery in Kubernetes
  • Database Resilience - automated horizontal scalability
  • Database Availability - what's the role of Kubernetes and the database
  • Utilizing both RAM and disk - set up Apache Ignite in a way to get in-memory performance with the durability of disk

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

Apache EU Roadshow, Berlin, Speaker - Akmal Chaudhri

June 14, 2018

This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources. In particular, attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark.

 

In-memory computing hot topics & emerging trends: Panel discussion in Menlo Park

Bay Area In-Memory Computing Meetup, Speaker - Denis Magda

June 13, 2018

While the cost of memory is still slightly higher than disk-based storage, an in-memory computing solution offers a tremendous increase in performance and much greater flexibility to incorporate new capabilities in the future. The benefit? A far superior return on investment (ROI), especially when competitive advantage and customer experience is taken into account.

You are invited to attend our June 13 gathering at BootUp in Menlo Park for an insightful panel discussion on in-memory computing hot topics and emerging trends (and more). The panel of experts will also field your questions, suggestions and ideas.

 

Skyrocket Java applications with the open-source Apache Ignite

Java Metroplex User Group (JavaMUG), Speaker - Dani Taphagen

June 13, 2018

In her talk, Dani will introduce the many components of the open-source Apache Ignite. As Java professionals, you will learn how to solve some of the most demanding scalability and performance challenges. She’ll also cover a few typical use cases and work through some code examples.

 

Adding Speed and Scale to Existing Applications with No Rip and Replace Using Apache® Ignite™

Webinar, Speaker - Denis magda

May 30, 2018

Learn how companies are not only adding speed and scale without ripping out, rewriting or replacing their existing applications and databases, but also how they're setting themselves up for future projects to improve the customer experience. This webinar will explain, with examples, how to:

  • Get started with Apache Ignite as In-Memory Data Grid (IMDG) deployed on top of RDBMS or NoSQL database
  • Keep data in sync across RAM (Apache Ignite) and disk (RDBMS/NoSQL database)
  • Leverage from Apache Ignite distributed SQL and ACID transaction for IMDG scenarios
  • Move further and start to build HTAP applications, real-time analytics, and machine learning, on the same IMDG

 

Improving Apache Spark™ In-Memory Computing with Apache Ignite™

Bay Area In-Memory Computing Meetup, Speaker - Valentin Kulichenko

May 17, 2018

Val will explain how Apache Ignite™ simplifies development and improves performance for Apache Spark™. He'll demonstrate how Apache Spark and Ignite are integrated, and how they are used to together for analytics, stream processing and machine learning. By the end of his presentation you'll understand:

  • How Apache Ignite’s native RDD and new native DataFrame APIs work
  • How to use Ignite as an in-memory database and massively parallel processing (MPP) style collocated processing for preparing and managing data for Spark
  • How to leverage Ignite to easily share state across Spark jobs using mutable RDDs and DataFrames
  • How to leverage Ignite distributed SQL and advanced indexing in memory to improve SQL performance

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

IOT World, Santa Clara Convention Center, CA, Speaker - Denis Magda

May 16, 2018

This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources. Attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark.

 

Machine Learning and Deep Learning with Apache® Ignite™

Webinar, Speaker - Akmal Chaudhri

May 16, 2018

Apache Ignite Release 2.4 added built-in machine learning (ML) and deep learning (DL). It not only eliminates any delays caused by transferring data to a different database or store. It delivers near real-time performance by running a variety of ML and DL algorithms in place, in memory, that are optimized for collocated processing. Learn more about these new capabilities and how to use them in Apache Ignite 2.4.

 

Comparing Apache Ignite and Cassandra for Hybrid Transactional/Analytical Processing (HTAP)

London In-Memory Computing Meetup, Speaker - Akmal Chaudhri

May 09, 2018

The 10x growth of transaction volumes, 50x growth in data volumes -- along with the drive for real-time visibility and responsiveness over the last decade -- have pushed traditional technologies including databases beyond their limits. Your choices are either buy expensive hardware to accelerate the wrong architecture, or do what other companies have started to do and invest in technologies being used for modern hybrid transactional/analytical processing (HTAP).

 

Comparing Apache Ignite and Cassandra for Hybrid Transactional/Analytical Processing (HTAP)

NYC In-Memory Computing Meetup, Speaker - Akmal Chaudhri

April 26, 2018

Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

  • The requirements for real-time, high volume HTAP applications
  • Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
  • A detailed comparison of Apache Ignite and GridGain® for HTAP applications

 

Improving Apache Spark™ In-Memory Computing with Apache Ignite™

Webinar, Speaker - Akmal Chaudhri

April 25, 2018

Learn how Apache Ignite™ simplifies development and improves performance for Apache Spark™. This session will explain how Apache Spark and Ignite are integrated, and how they are used to together for analytics, stream processing and machine learning. By the end of this session you will understand:

  • How Apache Ignite's native RDD and new native DataFrame APIs work
  • How to use Ignite as an in-memory database and massively parallel processing (MPP) style collocated processing for preparing and managing data for Spark
  • How to leverage Ignite to easily share state across Spark jobs using mutable RDDs and DataFrames
  • How to leverage Ignite distributed SQL and advanced indexing in memory to improve SQL performance

 

Comparing Apache Ignite and Cassandra for Hybrid Transactional/Analytical Processing (HTAP)

Bay Area In-Memory Computing Meetup, Speaker - Dmitriy Setrakyan

April 11, 2018

Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

  • The requirements for real-time, high volume HTAP applications
  • Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
  • A detailed comparison of Apache Ignite and GridGain® for HTAP applications

 

Apache Spark and Apache Ignite: Make streaming analytics real with in-memory computing

Apache Spark and Distributed Computing Maryland, Speaker - Akmal Chaudhri

April 05, 2018

Learn how Apache Spark is integrated with Apache Ignite through standard Spark APIs, and how Spark benefits from processing data in-memory in Apache Ignite. In this session Akmal will demonstrate how to:

  • Use Ignite as an in-memory database for Spark applications
  • Perform streaming analytics by deploying Spark stream pipeline
  • Process data stored in Ignite with Spark RDDs and DataFrames
  • Speed up SQL queries by leveraging the Ignite SQL engine and indexing

 

Apache Ignite: the in-memory hammer in your data science toolkit.

NOVA Data Science, Speaker - Akmal Chaudhri

April 04, 2018

In this presentation, Akmal will look at some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Faster data access and processing? Our experiment with Apache Ignite

DC Spring Framework Meetup, Speaker - Akmal Chaudhri

April 03, 2018

Slow database performance is a common complaint for Java developers. Is Apache Ignite the solution? Akmal Chaudhri will cover a few typical use cases and work through some code examples using Apache Ignite.

 

The In-Memory Hammer In Your Data Science Toolkit

Big Data, Washington DC v 2.0, Speaker - Akmal Chaudhri

April 02, 2018

In this presentation, Akmal will explain some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Comparing Apache® Ignite™ and Cassandra™ for Hybrid Transactional Applications (HTAP)

BrightTALK Webinar, Denis Magda

March 28, 2018

Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

  • The requirements for real-time, high volume HTAP applications
  • Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
  • A detailed comparison of Apache Ignite and GridGain® for HTAP applications

 

Comparing Apache® Ignite™ and Cassandra™ for Hybrid Transactional Applications (HTAP)

Webinar, Denis Magda

March 28, 2018

Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

  • The requirements for real-time, high volume HTAP applications
  • Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
  • A detailed comparison of Apache Ignite and GridGain® for HTAP applications

 

In-Memory Computing Essentials for Data Scientists

Symbion IoT Meetup (Copenhagen, Denmark), Speaker - Akmal Chaudhri

March 28, 2018

In this hands on workshop, attendees will be introduced to the fundamental capabilities of in-memory computing platforms that boost highly-loaded applications, research projects, risk analysis and fraud detection tasks by storing and processing massive amounts of data in memory and on disk across a cluster of machines.

 

Apache Ignite: the in-memory hammer in your data science toolkit

Symbion IoT Meetup (Copenhagen, Denmark), Speaker - Akmal Chaudhri

March 27, 2018

In this presentation, Akmal will explain some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

How to Share State Across Multiple Spark Jobs using Apache Ignite

Atlanta Apache Spark User Group, Speaker - Akmal Chaudhri

March 20, 2018

This session will demonstrate how to easily share state in-memory across multiple Spark jobs, either within the same application or between different Spark applications using an implementation of the Spark RDD abstraction provided in Apache Ignite

 

Apache Ignite: The in-memory hammer in your data science toolkit

Big Bang Data Science - Georgia, Speaker - Akmal Chaudhri

March 19, 2018

Join Big Bang Data Science as we learn from Dr. Akmal Chaudhri about some of the main components of Apache Ignite, such as the Compute Grid, Data Grid, and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Choosing the Right In-Memory Computing Technology

Webinar, Dmitriy Setrakyan

March 14, 2018

The need for real-time computing has resulted in the growth of many different in-memory computing technologies including caches, in-memory data grids, in-memory databases, streaming technologies and broader in-memory computing platforms. But what are the best technologies for each type of project? Learn about your options from one of the leading in-memory computing veterans.

 

All the Cool Kids are Doing it: The Whys and Hows of Architecting a Distributed Caching solution for your use case with Apache Ignite

NYC In-Memory Computing Meetup, Speaker - Fotios Filacouris

March 14, 2018

Are you considering a distributed cache to help accelerate and scale your existing application? Or do you have a new project that you know the SLAs are going to require an act of magic to produce? Have no fear, Foti is here to walk your through some reference architectures on various use cases that have benefited from using Apache Ignite. He will cover the Why and How of each use case and the pros and cons of different technology choices. How to use Kafka, noSQL, RDBMS, Kubernetes and container deployment, Spark, etc will all be discussed in terms of various best practices in architecting the right solution with Apache Ignite.

 

In-Memory Computing Essentials for Architects and Developers - Part 1

Moscow Apache Ignite Meetup, Speaker - Denis Magda

March 13, 2018

Denis Magda will talk about the main features and components of In-Memory Computing solutions using the example of Apache Ignite. The webinar combines theory and practice, after which participants will be able to design and write code for similar systems. On specific examples of the code you will learn about:

  • Configuration and launch of clusters
  • Data processing using key-value API
  • Optimal data processing with distributed SQL

This webinar is in Russian.

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

OpenIoTSummit North America, Speaker - Akmal Chaudhri

March 12, 2018

This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources. In particular, attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark.

 

In-Memory Computing Essentials for Java Developers

Amsterdam Java User Group Workshop, Speaker - Akmal Chaudhri

March 08, 2018

Akmal Chaudhri will introduce to the fundamental capabilities of in-memory computing platforms that boost high-load applications and services, and bring existing IT architecture to the next level by storing and processing a massive amount of data both in RAM and, optionally, on disk.

 

Catch an intro to the Java-powered Apache Ignite - memory-centric distributed platform

Amsterdam Java User Group, Speaker - Akmal Chaudhri

March 07, 2018

In his talk, Akmal will introduce the many components of the open-source Apache Ignite. You will learn how to solve some of the most demanding scalability and performance challenges. Akmal will also cover a few typical use cases and work through some code examples. Hope to see you there so you can leave ready to fire up your database deployments!

 

Distributed Database DevOps Dilemmas? Kubernetes to the rescue!

Amsterdam Kubernetes/Cloud-Native Meetup, Speaker - Akmal Chaudhri

March 06, 2018

Attendees will be introduced to the fundamental capabilities of in-memory computing platforms that boost highly-loaded applications, research projects, risk analysis and fraud detection tasks by storing and processing massive amounts of data in memory and on disk across a cluster of machines.

These capabilities and benefits will be demonstrated with the usage of Apache Ignite which is the in-memory computing platform that is durable, strongly consistent, and highly available with powerful SQL, key-value and processing APIs.

 

Skyrocket Java applications with the open-source Apache Ignite

The Brussels Java User Group, Speaker - Akmal Chaudhri

March 05, 2018

In his talk, Akmal will introduce the many components of the open-source Apache Ignite. As Java professionals, you will learn how to solve some of the most demanding scalability and performance challenges. He’ll also cover a few typical use cases and work through some code examples. Attendees would leave ready to fire up their own database deployments!

 

Basics of In-Memory Computing for architects and developers: Part 1

Webinar, Denis Magda

Febuary 28, 2018

Denis Magda will talk about the main features and components of In-Memory Computing solutions using the example of Apache Ignite. The webinar combines theory and practice, after which participants will be able to design and write code for similar systems. On specific examples of the code you will learn about:

  • Configuration and launch of clusters
  • Data processing using key-value API
  • Optimal data processing with distributed SQL

This webinar is in Russian.

 

The In-Memory Hammer In Your Data Science Toolkit

Big Data, Berlin, Speaker - Akmal Chaudhri

Febuary 22, 2018

In this presentation, Akmal will explain some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Building consistent and highly available distributed systems with Apache Ignite and GridGain

Bay Area In-Memory Computing Meetup, Speaker - Valentin Kulichenko

Febuary 21, 2018

In this session, meetup attendees will be given an overview of Apache® Ignite™ and GridGain capabilities that allow the delivery of high availability, while not breaking data consistency. Specific guidelines will be presented on how to build such systems covering topics such as:

  • In-memory backups
  • Data persistence
  • Data center replication
  • Full and incremental snapshots

 

Kubernetes: Good, Bad, Ugly of GKE and Distributed Databases in Kubernetes

Berlin Kubernetes Meetup, Speaker - Akmal Chaudhri

Febuary 21, 2018

In this talk you will learn how Kubernetes can orchestrate distributed database like Apache Ignite, in particular:

  • Cluster Assembling - database nodes auto-discovery in Kubernetes
  • Database Resilience - automated horizontal scalability
  • Database Availability - what’s the role of Kubernetes and the database
  • Utilizing both RAM and disk - set up Apache Ignite in a way to get in-memory performance with durability of disk

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

Index Developer Conference, Speaker - Denis Magda

Febuary 20, 2018

It is not enough to build a mesh of sensors or embedded devices to obtain more insights about the surrounding environment and optimize your production systems. Usually, your IoT solution needs to be capable of transferring enormous amounts of data to storage or the cloud where the data have to be processed further. This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources.

 

Skyrocket Java applications with the open-source Apache Ignite

Java Usergroup Berlin-Brandenburg, Speaker - Akmal Chaudhri

Febuary 20, 2018

In his talk, Akmal will introduce the many components of the open-source Apache Ignite. Meetup members, as Java professionals, will learn how to solve some of the most demanding scalability and performance challenges. He’ll also cover a few typical use cases and work through some code examples. Attendees would leave ready to fire up their own database deployments!

 

GridGain Webinar: Redis Replaced: Why Companies Now Choose Apache® Ignite™ to Improve Application Speed and Scale

Webinar, Denis Magda

Febuary 20, 2018

Learn why businesses are choosing Apache Ignite to handle their in-memory computing needs, and moving away from traditional caches like Redis. In this session, Denis will explain how:

  • In-memory technologies have evolved from caches to in-memory computing platform
  • Apache Ignite slides in-between existing applications and SQL databases to improve performance and scale
  • Apache Ignite native SQL and ACID transaction support works
  • Apache Ignite in-memory storage and collocated computing scales out linearly to avoid scale limitations with traditional caches

 

Deploy like a Boss: Using Kubernetes and Apache Ignite!

San Francisco Kubernetes Meetup, Speaker - Dani Traphagen

Febuary 15, 2018

If downtime is not an option for you and your application needs to be extremely low-latency; what cocktail of open source projects can facilitate this best? Both Kubernetes and Apache Ignite are Open Source Frameworks that work exceedingly well together to achieve said goals. By working with containerization Kubernetes helps enable developers to work seamlessly with new versions of their applications, running them where they want with a flexibly scalable experience. Apache Ignite is the perfect complement to this.

 

Getting Started with Apache® Ignite™ as a Distributed Database

Webinar, Valentin Kulichenko

Febuary 14, 2018

Apache Ignite native persistence is a distributed ACID and SQL-compliant store that turns Apache Ignite into a full-fledged distributed SQL database. In this webinar, Valentin Kulichenko will:

  • Explain what native persistence is, and how it works
  • Show step-by-step how to set up Apache Ignite with native persistence
  • Explain the best practices for configuration and tuning

 

Ignite your Cassandra Love Story: Caching Cassandra with Apache Ignite

Sydney Cassandra Users Meetup, Speaker - Rachel Pedreschi

Febuary 13, 2018

In this session you will learn how Apache Ignite can turbocharge your Cassandra cluster without sacrificing availability guarantees. In this talk we’ll cover:

  • An overview of the Apache Ignite architecture
  • How to deploy Apache Ignite in minutes on top of Cassandra
  • How companies use this powerful combination to handle extreme OLTP workloads

 

Java and In-Memory Computing: Apache Ignite

The Boston Java Meetup Group, Speaker - Fotios Filacouris

Febuary 13, 2018

In his talk, Akmal will introduce the many components of the open-source Apache Ignite. Meetup members, as Java professionals, will learn how to solve some of the most demanding scalability and performance challenges. He’ll also cover a few typical use cases and work through some code examples. Attendees would leave ready to fire up their own database deployments!

 

Turbocharge your MySQL queries in-memory with Apache Ignite

The Boston MySQL Meetup Group, Speaker - Fotios Filacouris

Febuary 12, 2018

Apache Ignite is a unique data management platform that is built on top of a distributed key-value storage and provides full-fledged MySQL support.Attendees will learn how Apache Ignite handles auto-loading of a MySQL schema and data from PostgreSQL, supports MySQL indexes, supports compound indexes, and various forms of MySQL queries including distributed MySQL joins.

 

Building consistent and highly available distributed systems with Apache Ignite and GridGain

London In-Memory Computing Meetup, Speaker - Akmal Chaudhri

Febuary 07, 2018

It is well known that there is a tradeoff between data consistency and high availability. However, there are many applications that require very strong consistency guarantees. Making such applications highly available can be a significant challenge. Akmal will explain how to overcome these challenges.

 

Apache Ignite Service Grid: Foundation of Your Microservices-Based Solution

DeveloperWeek 2018, Speaker - Denis Magda

Febuary 07, 2018

During this session, Denis will provide a step-by-step guide on how to build a fault-tolerant and scalable microservice-based solution using Apache Ignite's Service Grid and other components to resolve these aforementioned issues.

 

Meet Apache Ignite In-Memory Computing Platform

Tech it Easy- Tokyo, Speaker - Roman Shtykh

Febuary 01, 2018

In this talk you will learn about Apache Ignite memory-centric distributed database, caching, and processing platform. Roman will explain how one can do distributed computing, and use SQL with horizontal scalability and high availability of NoSQL systems with Apache Ignite.

 

Deploy like a Boss: Using Kubernetes and Apache Ignite!

Los Angeles Kubernetes Meetup, Dani Traphagen

January 31, 2018

If downtime is not an option for you and your application needs to be extremely low-latency; what cocktail of open source projects can facilitate this best? Both Kubernetes and Apache Ignite are Open Source Frameworks that work exceedingly well together to achieve said goals. By working with containerization Kubernetes helps enable developers to work seamlessly with new versions of their applications, running them where they want with a flexibly scalable experience. Apache Ignite is the perfect complement to this.

 

Ignite The Fire In Your SQL App

Webinar, Akmal Chaudhri

January 31, 2018

Apache Ignite is (an in-memory computing platform OR an in-memory distributed data store and compute grid) with full-fledged SQL, key-value and processing APIs. Many companies have added it as a cache in-between existing SQL databases and their applications to speed up response times and scale. In other projects they've used it as its own SQL database. This session will dive into some of the best practices for both types of projects using Apache Ignite.

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

Big Data Application Meetup, Speaker - Denis Magda

January 31, 2018

This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources.

 

Building consistent and highly available distributed systems with Apache Ignite and GridGain

NYC In-Memory Computing Meetup, Speaker - Akmal Chaudhri

January 25, 2018

It is well known that there is a tradeoff between data consistency and high availability. However, there are many applications that require very strong consistency guarantees, and making such applications highly available can be a significant challenge. In this session, attendees will be given an overview of Apache Ignite and GridGain capabilities that allow the delivery of high availability, while not breaking data consistency.

 

Scale Out and Conquer: Architectural Decisions Behind Distributed In-Memory Systems

Webinar, Denis Magda

January 17, 2018

Distributed platforms like Apache® Ignite™ rely on a horizontal “scale-out” architecture where you dynamically add more machines to achieve near-linear, elastic scalability. But how does it really work? What are its limits? And how can you optimize performance and scalability?

 

Getting Started With Apache Ignite

Nike Teck Talks, Speaker - Dani Traphagen

December 14, 2017

Apache Ignite provides a caching layer between applications and the system of record, but additionally, it provides a peer to peer architecture for transacting data, performing computations, microservices, streaming, and much more.

During this session, we will do a deep-dive into the Apache Ignite architecture and discuss how it is being deployed around the globe. You will walk away knowing why and when to use Apache Ignite in your next data intensive application!

 

Want extreme performance at scale? Do distributed the RIGHT way!

Bay Area In-Memory Computing Meetup, Speaker - Valentin Kulichenko

December 13, 2017

During this meetup, Valentin Kulichenko will talk about challenges and pitfalls one may face when architecting and developing a distributed system. Valentin will show how to take advantage of the affinity collocation concept that is one of the most powerful and usually undervalued technique provided by distributed systems. He will take Apache Ignite as a database for his experiments covering these moments in particular:

What is data affinity and why is it important for distributed systems? What is affinity colocation and how does it help to improve performance? How does affinity colocation affects execution of distributed computations and distributed SQL queries? And more...

 

In-Memory Computing Essentials for Architects and Developers: Part 2

Webinar, Denis Magda

December 13, 2017

In this webinar, Denis Magda will introduce the fundamental capabilities and components of a distributed, in-memory computing platform. With increasingly advanced coding examples, you’ll learn about:

  • Collocated processing
  • Collocated processing for distributed computations
  • Collocated processing for SQL (distributed joins and more)
  • Distributed persistence usage

 

Apache Ignite Use Cases for Banks and Telecoms

Moscow Apache Ignite Meetup, Speakers- Mikhail Kuznetzov, Mikhail Khasin, Victor Khoodyakov

December 12, 2017

Welcome to the inaugural gathering of the Moscow Apache® Ignite™ Meetup! Our guest experts - Mikhail Kuznetzov, Mikhail Khasin, and Victor Khoodyakov will talk about their experiences implementing solutions for a large bank as well as a telecom company, based on Apache Ignite.

 

Distributed Database DevOps Dilemmas? Kubernetes to the Rescue

KubeCon + CloudNativeCon North America 2017, Speaker - Denis Magda

December 08, 2017

Distributed databases can make so many things easier for a developer... but not always for DevOps. OK, almost never for DevOps. Kubernetes has come to the rescue with an easy application orchestration!

In this talk you will learn how Kubernetes can orchestrate distributed database like Apache Ignite, in particular:

  • Cluster Assembling - database nodes auto-discovery in Kubernetes.
  • Database Resilience - automated horizontal scalability.
  • Database Availability - what’s the role of Kubernetes and the database.
  • Utilizing both RAM and disk - set up Apache Ignite in a way to get in-memory performance with durability of disk.

 

Apache Ignite: the in-memory hammer in your data science toolkit

Austin Data Meetup, Speaker - Denis Magda

December 07, 2017

Machine learning is a method of data analysis that automates the building of analytical models. By using algorithms that iteratively learn from data, computers are able to find hidden insights without the help of explicit programming. These insights bring tremendous benefits into many different domains. For business users, in particular, these insights help organizations improve customer experience, become more competitive, and respond much faster to opportunities or threats. The availability of very powerful in-memory computing platforms, such as the open-source Apache Ignite (https://ignite.apache.org/), means that more organizations can benefit from machine learning today.

In this presentation, Denis will look at some of the main components of Apache Ignite, such as a distributed database, distributed computations, and machine learning toolkit. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Meeting the Challenges of Fast Data in Healthcare with In-Memory Technologies

Webinar, Akmal Chaudhri

December 06, 2017

In this webinar, Akmal Chaudhri will discuss the requirements for fast data in healthcare and specifically how Apache Ignite, a distributed in-memory computing platform, is used by drug discovery companies to identify potential therapies for complex diseases.

 

Implementing Durable Memory-Centric Architectures in Large Financial
Institutions

Webinar, Dmitriy Setrakyan

November 29, 2017

In this 1-hour webinar, GridGain Systems Chief Product Officer Dmitriy Setrakyan will present how distributed memory-centric architectures can be applied to various financial systems.

Dmitriy will first go over some Apache® Ignite™ features important for financial use cases, including ACID compliance, SQL compatibility, persistence, replication, security, fault tolerance and more. He will next analyze one of the largest Apache Ignite deployments in the world at Sberbank, a Russian and eastern European bank. He’ll walk through its overall architecture and demonstrate the 5 major challenges that Sberbank ran into when integrating distributed, horizontally scalable memory-centric database at their bank.

 

In-Memory Computing Essentials for Architects and Developers: Part 1

Webinar, Denis Magda

November 21, 2017

In this webinar, Denis Magda will introduce the fundamental capabilities and components of an in-memory computing platform, and demonstrate how to apply the theory in practice. With increasingly advanced coding examples, you’ll learn about:

  • Cluster configuration and deployment
  • Data processing with key-value APIs
  • Data processing with SQL

 

Hands-on Workshop: In-Memory Computing Essentials for Java Developers

Big Data and Cloud Meetup, Speaker - Denis Magda

November 16, 2017

Attendees will be introduced to the fundamental capabilities of in-memory computing platforms that boost high-load applications and services, and bring existing IT architecture to the next level by storing and processing a massive amount of data both in RAM and, optionally, on disk.

The capabilities and benefits of such platforms will be demonstrated with the usage of Apache Ignite, which is the in-memory computing platform that is durable, strongly consistent, and highly available with powerful SQL, key-value and processing APIs.

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

Devoxx Morocco, Speaker - Akmal Chaudhri

November 16, 2017

It is not enough to build a mesh of sensors or embedded devices to obtain more insights about the surrounding environment and optimize your production systems. Usually, your IoT solution needs to be capable of transferring enormous amounts of data to storage or the cloud where the data have to be processed further. Quite often, the processing of the endless streams of data has to be done in real-time so that you can react on the IoT subsystem's state accordingly.

This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources. In particular, attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark.

 

How to build an event-driven, dynamically re-configurable micro-services platform

Devoxx Belgium, Speaker - Sven Beauprez

November 10, 2017

Why only look at Apache Kafka to build event-driven microservices when there is also Apache Ignite, which brings far more to the table?

In this presentation, Sven will show you how to combine Apache Ignite with Docker to not only build an event-driven microservice platform but also to make this dynamically re-configurable without any downtime at all.

 

Apache Ignite: The In-Memory Hammer In Your Data Science Toolkit 

ODSC San Francisco, Speaker - Denis Magda

November 3, 2017

Machine learning is a method of data analysis that automates the building of analytical models. By using algorithms that iteratively learn from data, computers are able to find hidden insights without the help of explicit programming. These insights bring tremendous benefits into many different domains. For business users, in particular, these insights help organizations improve customer experience, become more competitive, and respond much faster to opportunities or threats. The availability of very powerful in-memory computing platforms, such as Apache Ignite, means that more organizations can benefit from machine learning today.

In this presentation Denis will look at some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Fast Data meets Big Data in the IoT- Using Apache Ignite 

Sydney IBM Bluemix Meetup Group, Speaker - Rachel Pedreschi

November 2, 2017

So, you've built yourself a killer IoT application. You have connected all the things and they are all happily sending over their packets of data faster than you can say "Big Blue". Now what? How do you architect a server architecture that can support all the data flowing in and also be able to grow for the future?

In this talk, Rachel will cover some of the architectural decisions you need to consider when choosing a data platform and discuss how Apache Ignite can meet those requirements. Rachel will also cover other design options like NoSQL and Spark and how to deploy in the IBM cloud.

 

Achieving High Availability and Consistency With Distributed Systems 

Bay Area Apache® Ignite™ Meetup, Speakers - Denis Magda, Valetin Kulichenko

November 2, 2017

Tech talk No. 1 - Val kicks off the learning with a session titled, "Building Consistent and Highly Available Distributed Systems with Apache Ignite and GridGain."

Tech talk No. 2 - Denis continues the knowledge sharing with a session titled, "Harnessing the 21st Century with a Distributed Memory-Centric SQL."

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT 

Dublin Spark Meetup, Speaker - Akmal Chaudhri

October 26, 2017

In this session, Akmal will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources. In particular, attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark.

 

How to Share State Across Multiple Spark Jobs using Apache® Ignite™ 

Spark Summit Europe 2017, Speaker - Akmal Chaudhri

October 25, 2017

Attend this session to learn how to easily share state in-memory across multiple Spark jobs, either within the same application or between different Spark applications using an implementation of the Spark RDD abstraction provided in Apache Ignite. During the talk, attendees will learn in detail how IgniteRDD – an implementation of native Spark RDD and DataFrame APIs – shares the state of the RDD across other Spark jobs, applications and workers. Examples will show how IgniteRDD, with its advanced in-memory indexing capabilities, allows execution of SQL queries many times faster than native Spark RDDs or Data Frames.

 

The In-Memory Computing Summit 2017 – North America 

South San Francisco Conference Center

October 24-25, 2017

There will be several highly technical talks about Apache Ignite at the 3rd-annual In-Memory Computing Summit Oct. 24-25 at the South San Francisco Conference Center. The IMC Summit is the only industry-wide event that focuses on the full range of in-memory computing-related technologies and solutions held in North America.

Check out the agenda here: https://www.imcsummit.org/us/agenda/schedule/day-1

 

Better Machine Learning with Apache® Ignite™ 

Eurostaff Big Data Meetup, Speaker - Akmal Chaudhri

October 19, 2017

The availability of very powerful in-memory computing platforms, such as Apache® Ignite™, means that more organizations can benefit from machine learning today. In this presentation, Akmal will discuss how the Compute Grid, Data Grid, and Machine Learning Grid components of Apache Ignite work together to enable your business to start reaping the benefits of machine learning.

Through examples, attendees will learn how Apache Ignite can be used for data analysis and be the in-memory hammer in your machine learning toolkit.

 

Catch an intro to Apache Ignite and skyrocket Java applications 

Java User Group Meetup, Speaker - Valentin Kulichenko

October 18, 2017

Join Valentin (Val) Kulichenko as he introduces the many components of the open-source Apache Ignite. You, as a Java professional, will learn how to solve some of the most demanding scalability and performance challenges. He will also cover a few typical use cases and work through some code examples. Hope to see you there so you can leave ready to fire up your database deployments!

 

Apache® Spark™ and Apache® Ignite™: Where Fast Data Meets the IoT 

Webinar, Denis Magda

October 18, 2017

During this 1-hour webinar, Denis Magda will discuss a Fast Data solution that can receive endless streams from the Internet of Things (IoT) and be capable of processing the streams in real-time using Apache Ignite’s cluster resources. You will also learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache® Spark™.

 

Apache Ignite™: The In-Memory Hammer in Your Data Science Toolkit 

ODSC Europe 2017, Speaker - Akmal Chaudhri

October 14, 2017

In this presentation, Akmal will show some of the main components of Apache Ignite™, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for data analysis.

 

Powering up banks and financial institutions with distributed systems 

Big Data Week London 2017, Speaker - Akmal Chaudhri

October 13, 2017

In this presentation, attendees will learn about important Apache Ignite features for financial applications, such as ACID compliance, SQL compatibility, persistence, replication, security, fault tolerance and more.

A customer case study will also be presented. We will analyze one of the largest Apache Ignite deployments in the world at Sberbank, a Russian and Eastern European Bank, by walking through the overall architecture and demonstrating various implementation and deployment challenges.

 

Real-time Data Analysis with Apache Ignite High-Performance In-memory Platform 

Data Platform Conference Tokyo 2017, Speaker - Roman Shtykh

October 10, 2017

With the advances in IoT technology, the volume and the diversity of data to be analyzed has enormously increased, and processing it with traditional disk-based technology has become more challenging. Therefore the number of data analysis solutions using in-memory technology, such as Apache Ignite high-performance in-memory platform, has increased.

In this session, Roman will introduce Apache Ignite, and explain how it can be used for real-time analysis of large volumes of IoT data.

 

Postgres with Apache® Ignite™: Faster Transactions and Analytics 

Webinar, Fotios Filacouris

October 4, 2017

Join Fotios Filacouris as he discusses how you can supplement PostgreSQL with Apache Ignite. You'll learn:

  • The strategic benefits of using Apache Ignite instead of Memcache, Redis®, GigaSpaces®, or Oracle Coherence™
  • How to overcome the limitations of the PostgreSQL architecture for big data analytics by leveraging the parallel distributed computing and ANSI SQL-99 capabilities of Apache Ignite
  • How to use Apache Ignite as an advanced high-performance cache platform for hot data

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT 

Paris Spark Meetup, Speaker - Akmal Chaudhri

October 3, 2017

In this session, Akmal will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources. In particular, attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark.

 

Giving a boost to the Hadoop and Spark ecosystems with in-memory technologies 

Big Data & Data Science, Paris, Speaker - Akmal Chaudhri

October 2, 2017

In this talk, Akmal present how to speed up existing Hadoop and Spark deployments by making Apache Ignite responsible for RAM utilization. No code modifications, no new architecture from scratch! Specifically, this presentation will cover : Hadoop Accelerator, HDFS compliant In-Memory File System, MapReduce Accelerator, Spark Shared RDDs, Spark SQL boost.

 

Stateful Apps in Production and Distributed Database Orchestration 

New York Kubernetes Meetup, Speaker - Akmal Chaudhri

September 27, 2017

This talk will focus on a DevOps perspective on the orchestration of distributed databases, Apache Ignite. Denis will speak on node auto-discovery, automated horizontal scalability, availability and utilization of RAM and disk with Apache Ignite.

 

Better Machine Learning with Apache® Ignite™ 

Webinar, Akmal Chaudhri

September 27, 2017

In this presentation, Akmal will discuss how the Compute Grid, Data Grid, and Machine Learning Grid components of Apache Ignite work together to enable your business to start reaping the benefits of machine learning. Through examples, attendees will learn how Apache Ignite can be used for data analysis and be the in-memory hammer in your machine learning toolkit.

 

Powering up banks and financial institutions with distributed systems 

NYC In-Memory Computing Meetup, Speaker - Akmal Chaudhri

September 26, 2017

In this talk, Akmal will start with a brief high-level overview of distributed computing fundamentals and in-memory computing use cases. Then he'll introduce the open-source Apache Ignite, an in-memory computing platform that enables high-performance transactions, real-time streaming, and fast analytics in a single, comprehensive data access and processing layer.

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT 

Internet of Things (IoT) New York Meetup, Speaker - Akmal Chaudhri

September 25, 2017

Quite often, the processing of the endless streams of data has to be done in real-time so that you can react on the IoT subsystem's state accordingly. In this session, Akmal will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources.

 

Apache Spark, Apache Flink, and Apache Ignite: Where Fast Data Meets the IoT 

Meetup, San Francisco, CA, Speaker - Denis Magda

September 20, 2017

This session will show attendees how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite's cluster resources.

In particular, attendees will learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Flink.

 

Business Intelligence and Apache Ignite for .NET Users 

Meetup, Cambridge .NET User Group, Speaker - Akmal Chaudhri

September 18, 2017

This presentation will provide a deep dive into .NET features of the top level Apache projects: Apache Ignite. Apache Ignite is the memory-centric platform that combines distributed SQL database and key-value data grid, that is ACID compliant, horizontally scalable and highly available, and empowered with compute and machine learning capabilities.

 

Apache Ignite: The in-memory hammer in your data science toolkit 

Meetup, Mountain View, CA, Speaker - Denis Magda

September 13, 2017

In this talk, Denis will go through some of the main components of Apache Ignite, such as the Compute Grid, Data Grid and the Machine Learning Grid. Through examples, attendees will learn how Apache Ignite can be used for big data analysis.

 

Implementing In-Memory Computing for Financial Services Use Cases with Apache® Ignite™ 

Webinar, Denis Magda

September 12, 2017

In this presentation, Denis will explain features of the Apache Ignite distributed computing platform that are important for financial use cases, including:

  • ACID transaction guarantees
  • Distributed ANSI-99 SQL support
  • Replication
  • Security
  • Fault tolerance
  • Persistence

 

Apache Spark and Apache Ignite: Where Fast Data Meets the IoT 

Meetup, Santa Clara, CA, Speaker - Denis Magda

September 09, 2017

In his talk, Denis will will show attendees how to build a sast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using the cluster resources of Apache Ignite.

 

Deploy like a Boss: Using Kubernetes® and Apache® Ignite™ 

Webinar, Dani Traphagen

August 23, 2017

If downtime is not an option for you, and your application needs to be extremely low-latency, Kubernetes® and Apache® Ignite™ are open source frameworks that work exceedingly well together to achieve these goals.

In this webinar, Dani Traphagen will walk through the basics of a Kubernetes and Apache Ignite deployment, including:

  • Setting up a Apache Ignite cluster
  • Using the Kubernetes IP Finder and the Kubernetes Ignite Lookup Service
  • Sharing the Ignite Cluster Configuration
  • Deploying your Ignite Pods
  • Adjusting the Ignite Cluster Size when you need to scale

 

Introduction to Apache Ignite, a memory-centric distributed platform 

Webinar, Akmal Chaudhri

August 16, 2017

Apache Ignite is an open source memory-centric platform that combines a distributed SQL database with a Key-Value Data Grid that is ACID-compliant and horizontally scalable. It enables high-performance transactions, real-time streaming, and fast analytics in a single, comprehensive data access and processing layer.

In this webinar, attendees will learn about the many components of Apache Ignite, including the Data Grid, Compute Grid, distributed SQL database and the Machine Learning Grid. We will also cover a few typical use cases and work through some Java code examples.

 

Building Consistent and Highly Available Distributed Systems with Apache® Ignite™ 

Webinar, Valentin Kulichenko

August 02, 2017

In this session, Valentin Kulichenko, Apache Ignite Committer and PMC, will give an overview of some of Apache® Ignite™ capabilities that allow the delivery as much availability as possible, while not breaking data consistency. Valentin will give specific guidelines on how to build such systems, and will do a deep dive into topics like:

  • In-memory backups
  • Data persistence
  • Data center replication
  • Full and incremental snapshots

 

Diving into the internals of Apache Ignite's memory architecture 

Meetup, Denis Magda

Jul 27, 2017

Apache Ignite is one of the fastest growing Apache projects. The presentation will take the audience on a roadmap discovery of Ignite moving to a memory-centric storage model, supporting both, fast in-memory and durable on-disk data, and blending a distributed SQL database with an in-memory key-value data grid.

 

An Intro to Apache Ignite, the Memory-centric Distributed Platform 

Meetup, Akmal Chaudhri

July 26, 2017

Join Akmal Chaudhri as he introduces the many components of the open-source Apache Ignite. You, as a Java professional, will learn how to solve some of the most demanding scalability and performance challenges. He will also cover a few typical use cases and work through some code examples.

 

Distributed ACID Transactions in Apache Ignite 

Webinar, Akmal Chaudhri

July 19, 2017

During this session, Akmal Chaudhri will do a deep-dive on the architecture of Apache Ignite's ACID-compliant transactional subsystem, elaborating on the following:

  • Data consistency: one-phase and two-phase commit implementations.
  • Fault-tolerance: recovery protocol for running transactions.
  • Optimistic and Pessimistic transactions.
  • Deadlock-free transactions
  • Deadlock detection mechanism

 

Turbocharge your SQL queries in-memory with Apache® Ignite™ 

Meetup, Amsterdam, Netherlands, Speaker - Denis Magda

June 20, 2017 @6:30pm

During this session, Denis will explain how Apache Ignite handles auto-loading of SQL schema and data from MySQL, supports SQL indexes, compound indexes support, and various forms of SQL queries including distributed SQL joins. He will demostrate how to:

  • Import SQL schema from MySQL and preserve the data sets stored in MySQL and Apache Ignite in sync.
  • Connect to Apache Ignite from your favourite tool or application language using ODBC or JDBC driver and start talking to a clustered data using familiar statements like SELECT, UPDATE, DELETE or INSERT.
  • Boost application performance 1,000x and scale to over 1 billion transactions per second with in-memory storage of hundreds of TB's of data for your SQL-based applications.

 

Apache Ignite Community Meetup - An Overview of Donated Ignite Persistent Store Feature 

Meetup, GoToMeeting, Speaker - Denis Magda

June 16, 2017 @8:00am

Apache Ignite Community decided to gather and dive into the details of Ignite Persistent Store donation to the main code base. It’s planned to give a general overview of the store learning more about its main capabilities and features as well as go over implementation details referring to the source code. To join use the details below.

Please join my meeting from your computer, tablet or smartphone.
https://global.gotomeeting.com/join/818661157

You can also dial in using your phone.
United States: +1 (571) 317-3112

Access Code: 818-661-157

 

Apache Ignite and Apache Spark: This is Where Fast Data Meets the IoT 

Spark Summit 2017, San Francisco, CA. Speaker - Denis Magda

June 07, 2017 @3:20pm

During this session, Denis will explain and demonstrate how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time. In particular, you will learn the following:

  • Data streaming to an Apache Ignite cluster from embedded devices powered by Apache Mynewt.
  • Real-time data processing with Apache Spark and Apache Ignite.

 

Apache® Ignite™ 2.0: Prelude to a Distributed SQL Database 

Webinar, Denis Magda

June 07, 2017 @11:00am PT / 2:00pm ET

Apache Ignite 2.0 is a turnkey release which blends a distributed in-memory SQL database (IMDB) and an in-memory key-value data grid (IMDG) under one data management platform. It is also a necessary stepping stone ahead of Ignite 2.1 release which will be focused around the native disk persistence, allowing Ignite operate equally well in-memory and on-disk. You will learn how the off-heap memory architecture in Ignite has been re-engineered to better support SSD or Flash-based persistence. The new off-heap design uses a page-based approach with slab memory allocation, which may be optionally mapped to a persistent storage as is, without having to serialize or deserialize the data. The new architecture automatically handles memory fragmentation, significantly accelerates SQL, and almost completely removes costly garbage collection pauses. You will also learn how to create and alter SQL indexes at runtime, as well as utilize DDL to update distributed data sets using standard SQL syntax. We will also cover B+Tree data structures used to store SQL indexes off-heap.

 

Apache Ignite and Apache Spark: This is Where Fast Data Meets the IoT 

ApacheCon North America, Miami, FL. Speaker - Denis Magda

May 18, 2017 @2:40pm

During this session, Denis will explain and demonstrate how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time. In particular, you will learn the following:

  • Data streaming to an Apache Ignite cluster from embedded devices powered by Apache Mynewt.
  • Real-time data processing with Apache Spark and Apache Ignite.

 

Apache Ignite SQL Grid: Hot Blend of Traditional SQL and Swift Data Grid 

ApacheCon North America, Miami, FL. Speaker - Denis Magda

May 18, 2017 @10:00am

In-memory data grids bring exceptional performance and scalability gains to applications built on top of them. The applications truly achieve 10x more performance improvement and become easily scalable and fault-tolerant thanks to the unique data grids architecture. However, because of this particular architecture, a majority of data grids have to sacrifice traditional SQL support requiring application developers to completely rewrite their SQL-based code to support data grid specific APIs.

 

Apache Ignite and Apache Spark: Where Fast Data Meets the IoT 

Miami Hadoop User Group, Miami, FL. Speaker - Denis Magda

May 17, 2017 @6:00pm

During this session, Denis will explain and demonstrate how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time. In particular, you will learn the following:

  • Data streaming to an Apache Ignite cluster from embedded devices powered by Apache Mynewt.
  • Real-time data processing with Apache Spark and Apache Ignite.

 

Benchmarking: Apache Ignite Still Keeps Ahead Of Hazelcast 

Blog, Denis Magda

May 12, 2017

There's an ad saying that Hazelcast is up to 50% faster than Apache Ignite, but that may not be true anymore. Check out this benchmark to get the true story.

 

The next phase of distributed systems with Apache Ignite 

OSCON, Austin, TX. Speaker - Dani Traphagen

May 10, 2017 @5:05pm

Is memory the new disk? If so, what does this mean for the future of database systems and persistence as we know it? Will all our data(bases) still belong to us? Dani Traphagen explores the key paradigm shifts currently impacting those Fortune 500 companies that view disk as a bottleneck. Dani explains how to optimize toward the cache, leveraging it for low-latency, highly available microservices architectures with the hot-and-fresh-out-of-the-kitchen open source project Apache Ignite.

 

Apache® Ignite™: Real-Time Processing of IoT-Generated Streaming Data 

Webinar, Denis Magda

May 10, 2017 @11:00am

During this 1-hour webinar, Denis will explain and demonstrate how to build a fast data solution that can receive endless IoT-generated streams and process them in real-time using Apache Ignite's distributed in-memory computing platform. In particular, you will learn the following:

  • How to stream data to an Apache Ignite cluster from embedded devices
  • How to conduct real-time data processing on this stream using Apache Ignite

 

Apache Ignite 2.0 Released 

May 05, 2017

This major release was under the development for a long time. The community spent almost a year incorporating tremendous changes to the legacy Apache Ignite 1.x architecture. Curious why are we so boastful about this? Some of the main features of Apache Ignite 2.0 are:

  • Re-engineered Off-Heap Memory Architecture
  • Data Definition Language
  • Machine Learning Grid Beta - Distributed Algebra
  • Integration with Spring Data, Rocket MQ, Hibernate 5
  • Enchanced Inite.Net and Ignite C++ APIs

See release notes for a full list of the changes.

 

Accelerate MySQL® for Demanding OLAP and OLTP Use Cases with Apache® Ignite™ 

Percona Live 2017, Santa Clara, CA, USA. Speaker - Nikita Ivanov

April 25, 2017 @1:20pm PT

How to overcome the limitations of the MySQL architecture for big data analytics by leveraging the parallel distributed computing and ANSI SQL-99 capabilities of Apache Ignite. How to use Apache Ignite as an advanced high performance cache platform for hot data. The strategic benefits of using Apache Ignite instead of memcache, Redis®, Elastic®, or Apache® Spark™. At the end of the session, you will understand how incorporating Apache Ignite into your architecture can empower dramatically faster analytics and transactions when augmenting your current MySQL infrastructure.

 

Apache® Ignite™: An In-Memory Backbone for Microservices-Based Architectures 

Webinar, Denis Magda

April 19, 2017 @11:00am PT / 2:00pm ET

When systems that rely on microservices are used under high load or have to process rapidly growing volumes of data, they usually face the same issues and difficulties as applications that are not microservices-based. Disk-backed databases become a performance bottleneck as they can no longer keep up with growing volumes of data that have to be stored and processed in parallel. This degrades application performance and ultimately causes instability.
This webinar discusses how in-memory computing using Apache® Ignite™ can overcome the performance limitations common to microservices architectures built using traditional database architectures.

 

Scalability in Distributed In-Memory Systems 

JPoint 2017, Moscow, Russia. Speaker - Vladimir Ozerov

April 7, 2017 @15:30pm

In-memory computing frameworks and products rely on a simple horizontal scalability property - the more machines we have in a cluster the better the performance. However, a reasonable question arises. If I add a second machine to the cluster will I get 2x improvement? If there are 10 machines in a cluster should I expect overall 10x performance increase? Is it true and if, yes, if the guarantee meets all the time? Join Yakov on his talk to get answers on these questions and learn more about scalability and concurrency concepts implemented in Apache Ignite In-Memory Data Fabric.

 

Scalability in Distributed In-Memory Systems 

JBreak 2017, Novosibirsk, Russia. Speaker - Yakov Zhdanov

April 4, 2017 @15:15pm

In-memory computing frameworks and products rely on a simple horizontal scalability property - the more machines we have in a cluster the better the performance. However, a reasonable question arises. If I add a second machine to the cluster will I get 2x improvement? If there are 10 machines in a cluster should I expect overall 10x performance increase? Is it true and if, yes, if the guarantee meets all the time? Join Yakov on his talk to get answers on these questions and learn more about scalability and concurrency concepts implemented in Apache Ignite In-Memory Data Fabric.

 

Presenting Apache Ignite SQL Grid at PGConf US 2017 

Presentation, Denis Magda

March 30, 2017 @14:00pm EDT

Learn how to boost performance 1,000x and scale to over 1 billion transactions per second with in-memory storage of hundreds of TBs of data for your SQL-based applications. Apache Ignite is a unique NewSQL platform that is built on top of a distributed key-value storage and provides full-fledged SQL support. Denis will show how Apache Ignite handles auto-loading of SQL schema and data, SQL indexes, compound indexes support, and various forms of SQL queries including distributed SQL joins. It will be demonstrated how to connect to Apache Ignite from your favorite tool or application language using ODBC or JDBC driver and start talking to a clustered data using familiar statements like SELECT, UPDATE, DELETE or INSERT.

 

Presenting Apache Ignite SQL Grid at Big Data Bootcamp 

Presentation, Denis Magda

March 28, 2017 @1:00pm PT

In this presentation, Denis will introduce Apache Ignite SQL Grid component that combines the best of two worlds - performance and scalability of data grids and traditional ANSI-99 SQL support of relational databases. Moreover, Denis will take an existing application that works with a relational database and will show how to run it on top of Apache Ignite with minimum efforts.

 

Presenting Apache Ignite at Codemotion Rome 2017 

Presentation, Mandhir Gidda

March 24, 2017 @15:00pm

Join and learn about Apache Ignite which is a high-performance, integrated and distributed in-memory platform for computing and transacting on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based or flash technologies.

 

The Apache® Ignite™ SQL Grid: A Hot Blend of Traditional SQL and In-Memory Data Grids 

Webinar, Denis Magda

March 15, 2017 @11:00am PT / 2:00pm ET

During this webinar, Apache Ignite PMC chair Denis Magda will introduce the SQL Grid component of Apache® Ignite™. He will discuss:

  • ANSI-99 SQL queries including distributed joins
  • Creating and leveraging SQL indices
  • Data modification with ANSI-99 DML (INSERT, UPDATE, DELETE, etc.)
  • Using Apache Ignite's JDBC and ODBC drivers

 

Apache Ignite: Transform batch-based system into swift real-time solution 

Apache Ignite London Meetup

February 23, 2017

IHS Markit will present first on how they have been using Apache Ignite on several major projects. The 2nd part of the meetup will be led by Mandhir Gidda who's been working with in-memory technologies for nearly 10 years.

 

The Apache® Ignite™ Web Console: Automating RDBMS Integration 

Webinar, Denis Magda

February 15, 2017 @11:00am PT / 2:00pm ET

During this webinar, Apache Ignite PMC chair Denis Magda will demonstrate how Apache® Ignite™ Web Console enables automatic integration of Apache Ignite and your RDBMS. He will show you how to:

  • Import a RBMS schema and map it to the Apache Ignite caches
  • Setup indexes
  • Create a Java POJO
  • Download a ready-to-run Apache Ignite based project that will be fully integrated with the RDBMS

 

Deploying Apache® Ignite™ – Top 7 FAQs 

Webinar, Christos Erotocritou and Rachel Pedreschi

January 25, 2017 @11:00am PT / 2:00pm ET

Christos Erotocritou and Rachel Pedreschi have helped numerous customers get started with Apache® Ignite™ and GridGain. During this 1-hour webinar, they will share answers to the most common questions asked prior to deployment. They will also provide guidance that will save you time and make deploying Apache Ignite a more enjoyable experience.

 

Apache Ignite 1.8.0 

December 09, 2016

This new release includes SQL DML operations support (INSERT, UPDATE, DELETE, MERGE) in Java, MapR distribution support in Hadoop, Entity Framework 2nd level cache and ASP.NET session state cache in .NET, DML and distributed joins in ODBC, stability and performance improvements, and more.

Download Ignite 1.8.0

Shared Memory Layer for Spark Applications 

Dmitriy Setrakyan, Apache Big Data Europe

November 16, 2016

Join Dmitriy Setrakyan, Apache Ignite Project Management Committee Chairman and co-founder and Chief Product Officer at GridGain, to learn more about the need to share state across different Spark jobs and applications and several technologies that make it possible, including Tachyon and Apache Ignite.

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Shared Memory Layer and Faster SQL for Spark Applications 

Dmitriy Setrakyan, Apache Big Data Europe

November 16, 2016

Learn the importance of In Memory File Systems, Shared In-Memory RDDs with Apache Ignite, as well as the need to index data in-memory for fast SQL execution.

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Apache Ignite - Path to Converged Data Platform 

Dmitriy Setrakyan, Apache Big Data Europe

November 15, 2016

The presentation will take the audience on a roadmap discovery of Ignite moving to a converged storage model, supporting both, analytical and transactional data sets.

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Apache Ignite 1.7.0 

August 05, 2016

This new release includes support for distributed SQL JOIN, decimal support in ODBC, custom affinity functions and ASP.NET Output Cache Provider in .NET, stability and performance improvements, and more.

Download Ignite 1.7.0

Apache Ignite London Meetup 

July 13, 2016

Join us for a technical session to look at Apache Ignite and hear from BlackRock on how they believe it will solve their application performance & scalability challenges.

Please RSVP on Meetup.com.

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Apache Ignite NYC Meetup 

June 28, 2016

Apache Ignite PMC member, Nikita Ivanov will be presenting a deep dive on Apache Ignite at our NYC meetup, Tuesday, June 28 at Work Market, 240 W 37th St, 9th Floor, New York, NY.

Please RSVP on Meetup.com. Space is limited and is filling up fast!

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Apache Ignite 1.6.0 

May 23, 2016

This new release includes support for deadlock detection in Ignite caches, ODBC driver, CacheStore implementation backed by Cassandra DB, AtomicSequence and AtomicReference data structures for .NET, transactions API for C++ client, stability and fault-tolerance improvements, and more.

Download Ignite 1.6.0

Ignite Adds Add-ons 

February 17, 2016

Add-ons has been added to the website for projects built on top of Ignite. These projects intend to make user experience with Ignite easier. Currently, there are two such projects available - Apache Ignite Extensions and GridGain Web Console.

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Apache Ignite 1.5.0.final Released 

January 4, 2016

This final version of 1.5.0 includes support for .NET and C++, Streamer for MQTT, Twitter, Apache Flume, and Apache Camel, OSGi support, "deadlock-free" transactions, compact binary protocol, performance improvements for SQL queries, transactions, and more.

Download Ignite 1.5.0.final

Apache Ignite 1.5.0-b1 Early Access Released 

December 12, 2015

This early access version includes support for .NET and C++, Streamer for MQTT, Twitter, and Apache Flume, compact binary protocol, performance improvements for SQL queries, transactions, and more.

Download Ignite 1.5.0-b1

Apache Ignite 1.4.0 Released 

September 28, 2015

This is the first Apache Ignite release since the project graduated from incubation in August, 2015. This new release includes SSL support to communication and discovery, support for log4j2, significantly faster JDBC driver implementation, fixes for SQL queries group index logic, auto-retries for cache operations in recoverable cases and more.

Download Ignite 1.4.0

Apache Ignite Graduated to a Top-Level Project 

August 25, 2015

The Apache Software Foundation (ASF), the all-volunteer developers, stewards, and incubators of more than 350 Open Source projects and initiatives, announced today that Apache™ Ignite™ has graduated from the Apache Incubator to become a Top-Level Project (TLP), signifying that the project's community and products have been well-governed under the ASF's meritocratic process and principles.

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Apache Ignite 1.3.0 Released 

July 21, 2015

This new release includes integration with Apache YARN for data center and resource management, fixes for JTA transactions, Hibernate L2 Cache improvements, and more.

Download Ignite 1.3.0

Apache Ignite 1.2.0 Released 

June 29, 2015

This new release includes shared RDD for Apache Spark (based on Ignite Data Grid), integration with Apache Mesos for data center management, client-mode for light-weight cluster discovery, memory-size eviction policy, and more.

Download Ignite 1.2.0

Apache Ignite 1.1.0 Released 

May 28, 2015

This new release includes Google Compute Engine and generic cloud TCP discovery IP finder, "Collocated" mode for SQL queries, support for (*) star notation in cache names, fix for SQL union support, and more.

Download Ignite 1.1.0

Apache Ignite 1.0.0 Released 

April 2, 2015

This new release includes dynamic caching functionality to start and stop caches during runtime, simplified Query API, automatic aggregation, grouping and sorting support for SQL Queries, Streaming examples, and more.

Download Ignite 1.0.0

Apache Ignite 1.0.0-RC3 Released 

March 24, 2015

This is the first release of Apache Ignite project. The source code in large part is based on the GridGain In-Memory Data Fabric, open source edition, v. 6.6.2, which was donated to Apache Software Foundation. The main feature set of Ignite In-Memory Data Fabric includes:

  • Advanced Clustering
  • Compute Grid
  • Data Grid
  • Service Grid
  • IGFS - Ignite File System
  • Distributed Data Structures
  • Distributed Messaging
  • Distributed Events
  • Streaming & CEP

Download Ignite 1.0.0-RC3

InfoQ Interview with Nikita Ivanov on Apache Ignite Incubation 

December 3, 2014

InfoQ caught up with Nikita Ivanov, CTO and founder of GridGain, about the In-Memory Computing framework becoming an Apache project, motivation behind this decision, and upcoming features and enhancements of GridGain.

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Apache Ignite Enters Incubation 

October 1, 2014

GridGain recently announced that the GridGain In-Memory Data Fabric has been accepted into the Apache Incubator program under the name "Apache Ignite." Earlier in 2014, GridGain was transformed to an open source model through Apache 2.0 license. Now, the product will be available under the Apache Foundation project portfolio.

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