Apache Ignite Blog Posts
Getting Started With Apache Ignite (Part 3)By Akmal Chaudhri | June 18, 2017
Get a brief look at the Apache Ignite Compute Grid component and learn how it ensures that tasks can be executed in parallel within the grid.
Getting Started With Apache Ignite (Part 2)By Akmal Chaudhri | June 04, 2017
In Apache Ignite, a data grid can be thought of as a distributed Key-Value (K-V) store or a distributed HashMap. Learn more about it in this article.
ADO.NET as Ignite.NET Cache StoreBy Pavel Tupitsyn | May 31, 2017
Learn about implementing an efficient Ignite.NET persistent store with ADO.NET and SQL Server, continuing from a previous article on the entity framework cache store.
Getting Started With Apache Ignite (Part 1)By Akmal Chaudhri | May 29, 2017
In this series of articles, I will share what I learned about Apache Ignite as a beginner, starting with clustering and deployment.
How to Monitor Mulitple Apache Ignite ClustersBy Prachi Garg | May 24, 2017
With its latest release, Apache Ignite 2.0 introduced support for DDL, a redesigned off-heap memory architecture, distributed algebra, Spring data integration, support for Hibernate 5, Rocket MQ Integration, as well as plenty of improvements to the currently existing Apache Ignite feature set to enhance speed and performance. Another key feature rolled in is multi-cluster support for Apache Ignite Web Console, which means you can monitor and manage multiple Ignite clusters in parallel from a single instance of Ignite Web console deployed on your system.
This tutorial shows how to start two separate clusters on your system and connect it to an instance of Ignite Web Console deployed locally.
Benchmarking: Apache Ignite Still Keeps Ahead Of HazelcastBy 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.
What's new in Apache Ignite.NET 2.0By Pavel Tupitsyn | May 12, 2017
Apache Ignite 2.0 has been released last week. Changes on Java side are tremendous, but Ignite.NET has some cool things to offer as well. Read on to to find out more.
An impatient start with Apache Ignite machine learning gridBy Shamim Bhuyian | May 12, 2017
Recently Apache Ignite 2.0 introduced a beta version of the in-memory machine learning grid, which is a distributed machine learning library built on top of the Apache IMDG. This beta release of ML library can perform local and distributed vector, decompositions and matrix algebra operations. The data structure can be stored in Java heap, off-heap or distributed Ignite caches. In this short post, we are going to download the new Apache Ignite 2.0 release, build the example and run them.
Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine LearningBy Denis Magda | 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.
Apache Ignite: Build Cloud Ready Applications Today!By Turik Campbell | May 02, 2017
All applications fundamentally are comprised of computing instructions and data the instructions utilize to solve a problem. These applications are high performant when computing instructions and data are distributed among available computing resources. A ‘cloud ready’ application should be able to:
- Massively parallelize compute instructions.
- Massively parallelize data.
- Scale automatically as hardware resources are introduced into the network.
Light a fire under Cassandra with Apache IgniteBy Nikita Ivanov | April 27, 2017
Over time as business requirements evolve and Cassandra deployments scale, many organizations find themselves constrained by some of Cassandra’s limitations, which in turn restrict what they can do with their data. Apache Ignite, an in-memory computing platform, provides these organizations with a new way to access and manage their Cassandra infrastructure, allowing them to make Cassandra data available to new OLTP and OLAP use cases while delivering extremely high performance.
Microservices on Top of an In-Memory Data Grid: Part IIIBy Denis Magda | April 26, 2017
This is the last blog post in a series recommending how to design and implement microservices-based architecture on top of Apache Ignite In-Memory Data Fabric. The first two posts in the series can be found here:
- Part I - Overview of the proposed solution.
- Part II - Various coding templates needed to implement the solution in a live environment.
This final post describes how to integrate the cluster with a persistent store and send requests to the microservices from external applications -- apps that know nothing about the cluster and don't rely on its APIs.
LINQ vs. SQL in Ignite.NET: PerformanceBy Pavel Tupitsyn | March 29, 2017
Ignite.NET offers a LINQ provider which translates C# expressions to SQL queries. LINQ has many benefits over SQL — but at what cost? Read on to find out.
Getting Started with Apache Ignite - Part 1By Dani Traphagen | March 29, 2017
My best definition of Apache Ignite is that it's a distributed in-memory cache, query and compute engine built to work with large-scale data sets in real-time. A cluster of Ignite nodes (which is simply a combination of server and client nodes) will slide between the application and data layers.
Deploying Apache Ignite in Kubernetes on Microsoft AzureBy Denis Magda | March 21, 2017
Apache Ignite's most recent release includes a Kubernetes integration. See it in action as you learn to run a cluster on Microsoft Azure.
Continuous Queries in Apache Ignite C++ 1.9By Igor Sapego | March 21, 2017
Apache Ignite 1.9 was released last week and it brings some cool features. One of them is Continuous Queries for Apache Ignite C++ that allows you to track data modifications on caches.
Modern Application Design With In-Memory Data FabricsBy Shamim Bhuiyan | March 16, 2017
In-memory grids like Apache Ignite have served as an essential, architectural component for transforming the way businesses use their data to do business.
What's New in Apache Ignite.NET 1.9By Pavel Tupitsyn | March 14, 2017
The newest version of Apache Ignite includes TransactionScope API, Distributed DML, and LINQ improvements. Read on to find out how these functionalities can provide enhanced transactional and SQL capabilities.
Apache Ignite 1.9 Release HighlightsBy Denis Magda | March 06, 2017
Apache Ignite community released a new version of Apache Ignite In-Memory Data Fabric. Learn more about improvements available in version 1.9.
Book Review: High Performance In-Memory Computing With Apache IgniteBy Shamim Bhuiyan | February 16, 2017
The Apache Ignite platform is very big and growing day by day. This book focuses on features of Apache Ignite that help improve application performance.
The ASF asks: Have you met Apache Ignite?By Sally Khudairi | January 18, 2017
Did you know that numerous Fortune 500 enterprises depend on Apache Ignite's in-memory data platform to process large-scale data sets in real-time, at orders of magnitude faster than traditional technologies?
Running Microservices on Top of In-Memory Data Grid: Part IIBy Denis Magda | January 18, 2017
Let's look into the Apache Ignite Cluster Layer, a GitHub project that includes the basic building blocks needed to implement a proposed microservices-based architecture.
Book: High performance in-memory computing with Apache Ignite has been publishedBy Shamim Bhuiyan | January 09, 2017
This book wraps all the topics like in-memory data grid, highly available service grid, streaming and in-memory computing use cases from high-performance computing to get the performance gain.
Enabling Access to Apache Ignite via Redis ProtocolBy Roman Shtykh | January 09, 2017
The Apache Ignite versions have the ability to store and retrieve data in the grid using any Redis client. Let's make connections to an Ignite cluster and do Redis string operations.
Apache Ignite Enables Full-fledged SQL Support for PHPBy Denis Magda | December 27, 2016
It's time to get your SQL statements and queries up and running on Apache Ignite's PHP offerings. You'll need a driver and some setup, but it's quick and easy.
Using the GridGain Web Console for Automatic RDBMS Integration With Apache IgniteBy Prachi Garg | December 19, 2016
Apache Ignite can import database schemas and automatically generate all the required XML OR-mapping configurations and Java domain model POJOs that you can easily download and copy into your Apache Ignite project.
Geospatial Queries With Apache IgniteBy Denis Magda | December 16, 2016
Storing and querying location data can be useful for any number of apps for projects. Apache Ignite has a geospatial component made just for that.
What's New in Apache Ignite.NET 1.8By Pavel Tupitsyn | December 14, 2016
The newest version of Apache Ignite includes an entity framework second-level cache, ASP.NET session state cache, custom logging, and LINQ improvements.
Apache Ignite With JPA: A Missing ElementBy Shamim Bhuiyan | December 07, 2016
Learn how to persist your entities with Apache Ignite and JPA. This tutorial will guide you through the setup of execution of that handy ability.
Entity Framework As Ignite.NET Cache StoreBy Pavel Tupitsyn | October 27, 2016
Learn how to implement Ignite.NET persistent store with Entity Framework and SQL Server.
Running Microservices on Top of In-Memory Data Grid: Part IBy Denis Magda | October 26, 2016
With this post, we start a series that will provide a guide on building a fault-tolerant, scalable, microservice-based solution with Apache Ignite In-Memory Data Fabric.
Ignite.NET Serialization PerformanceBy Pavel Tupitsyn | October 04, 2016
How fast are different Ignite serialization modes? How do they compare to other popular serializers? Find out in this blog by Pavel Tupitsin.
Deadlock-Free Transactions with Apache IgniteBy Prachi Garg | September 21, 2016
Deadlocks can kill services, so see how Apache Ignite avoids it by assigning numbers to transactions in order to compare and utilize them in a fluid manner.
ASP.NET Distributed Output Cache with Apache IgniteBy Pavel Tupitsyn | September 19, 2016
You can speed up your ASP.NET web farm with Apache Ignite distributed caching. Read on to learn more.
Building a Multi-Platform Ignite Cluster: Java + .NETBy Pavel Tupitsyn | September 09, 2016
Ignite cluster can consist of nodes on any supported platform: Java, .NET, and C++. This example shows you how to run a .NET/Java cluster with NuGet and Maven.
Apache Ignite 1.7: Welcome Non-Collocated Distributed Joins!By Denis Magda | August 24, 2016
Apache Ignite 1.7.0 has been recently rolled out, and among the new changes, you can find a killer one that was awaited by many Apache Ignite users and customers for a long time — Non-Collocated Distributed Join support for SQL queries.
Using Apache Ignite.NET in LINQPadBy Pavel Tupitsyn | August 19, 2016
Here is a quick how-to for using Apache Ignite.NET in LINQPad.
What's New in Apache Ignite.NET 1.7By Pavel Tupitsyn | August 09, 2016
Apache Ignite.NET 1.7 brings some pretty cool new features. Read on to find out more!
Getting Started with Apache Ignite.NET Part 3: Cache QueriesBy Pavel Tupitsyn | July 28, 2016
In Part 3 of Pavel Tupitsyn's series, he covers the cache queries: Scan, SQL, LINQ, and Text.
Getting Started with Apache Ignite.NET Part 2: Distributed CacheBy Pavel Tupitsyn | July 16, 2016
Learn the cache operations and object serialization of Apache Ignite.NET.
Getting Started with Apache Ignite.NET Part 1By Pavel Tupitsyn | June 25, 2016
Learn the basics of using Apache Ignite.NET, from an explanation about the terminology to helpful code snippets illustrating the instructions.
Real-time In-memory OLTP and Analytics with Apache Ignite on AWSBy Babu Elumalai | June 06, 2016
This post shows you how to build a Lambda architecture using Apache Ignite, and provides some examples explaining how to perform ANSI SQL on real-time data and how to use it as a cache for OLTP reads.
Apache Ignite: How to Read Data from Persistent StoreBy Prachi Garg | June 03, 2016
A tutorial on how to load data from a MySQL database into an Ignite distributed cache.
Pitfalls of the MyBatis Caches with Apache IgniteBy Shamim Bhuiyan | March 09, 2016
A tutorial on how to look at cache entries in Apache Ignite.
A Universal Streamer for Apache Ignite based on Apache CamelBy Raúl Kripalani | January 28, 2016
Apache Ignite has the concept of Data Streamers: components to ingest fast data in a streaming fashion into an Ignite cache from a variety of protocols, technologies or platforms, such as JMS, MQTT, Twitter, Flume, Kafka, etc. However, with Apache Ignite 1.5.0 we released the jack of all trades: an Apache Camel streamer.
Apache Ignite: Distributed In-Memory Key-Value StoreBy Prachi Garg | January 27, 2016
For systems where low latency is critical, there is nothing better than caching the data in memory in a distributed cluster. While storing data in memory provides fast data access, distributing it on a cluster of nodes increases application performance and scalability. And Apache Ignite helps you achieve exactly that.
Getting Started with Apache IgniteBy Prachi Garg | December 19, 2015
This tutorial shows you how to create a simple "Hello World" example in Apache Ignite.
Apache Ignite for Database CachingBy Prachi Garg | Septmeber 23, 2015
A tutorial on how to use Apache Ignite for caching RDBMS, NoSQL, or HDFS databases.
How Apache Ignite Processes Geographically Distributed TransactionsBy Yakov Zhdanov | July 22, 2015
Imagine a bank offering variety of services to its customers. The customers of the bank are located in different geo-zones (regions), and most of the operations performed by a customer are zone-local, like ATM withdrawals or bill payments... However, some operations, such as wire transfers for example, may affect customers across different zones. Cross-zone operations are not as frequent, but nevertheless need to be supported in a transactional fashion as well.