Download Ignite 2.13.0

In-Memory Database
With Apache Ignite

In-memory database that scales horizontally across memory
and disk with full SQL support
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In-Memory Database Overview

What is an in-memory database?

An in-memory database (IMDB) is a data management system that stores data primarily in the computer’s main memory.

How does an in-memory database work?

In-memory databases rely on spinning disks for data storage. IMDBs allow mission-critical applications to benefit from faster response times than disk-based databases.

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Apache Ignite as a distributed in-memory database scales horizontally across memory and disk without compromise

Apache Ignite works with memory, disk, and Intel Optane as active storage tiers.

This multi-tier architecture combines the advantages of in-memory computing with disk durability and strong consistency, all in one system.

Speed of memory

Strong consistency

Durability of disk

Advantages Of Ignite Multi-Tiered Architecture

Instantaneous cluster restarts

Ignite becomes fully operational from disk upon a cluster startup or restarts without requiring a preload or a warm-up the memory tier.

Multi-tiered storage

Ignite treats disk as an active storage layer, allowing it to cache a subset of the data in memory and query both in-memory and disk-only records with SQL and all other available APIs.

Apache Ignite as an in-memory database
supports a variety of developer APIs

Essential Developer APIs

sql
SQL
apis
Key-value
acid
ACID
transactions

Enable you to request, join, and group distributed datasets.

High-Performance Computing APIs

sql
Compute
apis
Machine
learning
acid
Services

Execute logic close to the data, thus eliminating expensive data shuffling over the network.

Real-Time Streaming APIs

sql
Streaming
apis
Continuous
Queries
acid
Messaging

Allow the seamless implementation of event-driven architectures.

In-Memory Database Ignite User Stories

BNP Paribas

with the help of Apache Ignite managed to design, build, and optimize a hybrid transactional-analytical processing (HTAP) solution. This enabled the bank to make key business decisions in real time.

JP MorganChase

faced an increasing need to apply transformations to large datasets in real time. To meet this need, their team selected Ignite to achieve persistence, caching and integrated compute.

Ready to Start?

Discover our quick start guide and build your first
application in 5-10 minutes

Quick Start Guide