GridGain and Hazelcast IMDG Feature Comparison

Hazelcast® IMDG is an in-memory data grid that is used by companies to improve application speed and scale. Hazelcast, the company, offers both a commercially supported version and an open source version of Hazelcast IMDG under the Apache® License 2. However, Hazelcast IMDG is not an Apache Software Foundation project.

GridGain®, built on the Apache® Ignite open source project, is an in-memory computing platform that includes a distributed in-memory data grid (IMDG), a SQL and key-value in-memory database, a stream processing and analytics engine, and a continuous learning framework for machine and deep learning. GridGain Systems donated the original code to the Apache Ignite project and is the largest contributor.

Hazelcast and GridGain both support in-memory data grid use cases and provide strong performance and scalability. But Hazelcast is only a viable contender as an in-memory data grid for new Java-based applications. In almost every other IMDG and in-memory computing use case GridGain is better. Because GridGain is a platform, it is also a better choice for common in-memory computing infrastructure.

Major Advantages of GridGain vs. Hazelcast IMDG

  • ANSI-99 SQL Support
  • Distributed ACID Transaction Support
  • Slides In-between SQL-based Applications and RDBMSs with No Custom Coding
  • Cross-Language Support for Collocated Processing (Java, .NET and C++)
  • Native Integration with RDBMSs, NoSQL Databases and Hadoop
  • Comprehensive In-Memory Computing Solution
  • Support for Apache® Spark™ DataFrames, RDDs and HDFS
  • Built-in Machine Learning and Deep Learning

Detailed GridGain and Hazelcast Feature Comparison

This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Hazelcast (and their respective open source projects where relevant) compare in 25 different categories including:

Feature GridGain PE 2.4
Apache Ignite 2.4
GridGain EE 8.4 GridGain UE 8.4 Hazelcast Enterprise 3.10
In-Memory Data Grid
Third Party Database Caching and Persistance (inline)
SQL Database
(+ Multi-datacenter data and disaster recovery management)
 
In-Memory Database
(+ Multi-datacenter data and disaster recovery management)
 
Web Session Clustering
Apache Spark Acceleration  
Hadoop Acceleration  
In-Memory File System (Hadoop Compliant)  
Third Party Database Support, Persistance
Inline Support for Leading RDBMSs (Oracle, IBM DB2, Microsoft SQL Server, MySQL, Postgres, ... ) (It works well, but requires coding to implement, it's not out of the box)
Inline Support for Cassandra  
Inline Support for MongoDB  
Write Through and Read Through
  • Use Cases
  • 3rd Party Database Support and Persistence
  • Support for Native Persistence
  • Distributed SQL and Queries
  • ACID Compliant Transactions and Locks
  • Memory Architecture and Optimization
  • Distributed Architecture
  • Data Rebalancing
  • Distributed Computing
  • In-Memory Streaming and Integration with Apache Spark
  • Security and Audit
  • Configuration and Grid Management
  • Supported Platforms, Standards and Out-of-the-Box Integration
  • Cloud and Virtualization Support
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