GridGain and Hazelcast IMDG Feature Comparison

Compare GridGain (built on Apache Ignite) and Hazelcast IMDG across SQL, ACID transactions, integrations, multi-language compute, streaming, and enterprise readiness.

  • Compare ANSI-99 SQL support and distributed SQL joins
  • Evaluate distributed ACID transactions, isolation levels, and cross-partition support
  • See how GridGain “slides in” without custom coding
  • Review RDBMS/NoSQL/Hadoop integrations, plus Spark and HDFS support
  • Compare off-heap memory, tiered storage, and persistence capabilities
  • Assess machine learning, deep learning, and collocated compute support

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About this feature comparison

This feature comparison summarizes differences between the GridGain in-memory computing platform and Hazelcast IMDG for in-memory data grid (IMDG) use cases, including where each is positioned for production deployment.

The paper highlights several core differentiators: native ANSI-99 SQL (including distributed JOINs), distributed ACID transactions with multiple isolation levels, and GridGain’s ability to accelerate SQL-based applications by replacing existing JDBC/ODBC drivers—positioned as configuration-first rather than extensive code changes.

It also compares platform breadth. GridGain is described as a broader in-memory computing platform (IMDG + in-memory SQL/key-value database + streaming/analytics), with native integrations for RDBMSs/NoSQL/Hadoop and broader support for collocated processing (MPP) across Java, .NET, and C++. Hazelcast is positioned primarily as an IMDG with more limited support in several of these areas.

GridGain supports ANSI-99 compliant SQL, including distributed SQL JOINs… Hazelcast requires developers to change existing applications.

GridGain and Hazelcast IMDG Feature Comparison

Compare GridGain (built on Apache Ignite) and Hazelcast IMDG across SQL, ACID transactions, integrations, multi-language compute, streaming, and enterprise readiness.Compare ANSI-99 SQL support and distributed SQL…

Get the full comparison