GridGain and Terracotta Feature Comparison

The Software AG Terracotta® BigMemory Max data management platform is used by companies to deliver low, predictable latency at any scale for applications. There is also a single server version, BigMemory Go, which is not considered here in part because it has a subset of the functionality of BigMemory Max. BigMemory includes Terracotta EHCache, which is available both as a commercial version and as open source under the Apache® 2.0 license.

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 hybrid SQL and key-value in-memory database (IMDB), a stream processing and analytics engine, and a continuous learning framework that supports real-time machine and deep learning. It can be used with any RDBMS, NoSQL or Hadoop database .

Terracotta has many of the core capabilities expected in an IMDG, including the ability to distribute and partition data, and scale out across a cluster. But Terracotta hasn’t evolved much in the years since Software AG acquired Terracotta. Five years after the release of BigMemory 4.0, the current release is 4.3.5. Even EHCache, which exists under an Apache 2.0 license, has not evolved much in comparison to other caching and IMDG vendors.

GridGain is better than Terracotta in almost every IMDG use case. This is due, in part to the innovation that comes from being built on Apache Ignite. GridGain Systems donated the original Apache Ignite code to the Apache Software Foundation (ASF) in 2014 and remains the most active contributor. Ignite became a top level ASF project in 2015. It is now one of the top five Apache Software Foundation open source projects in commits and list activity.

Major Advantages of GridGain vs. Terracotta

  • Comprehensive in-memory computing platform
  • Native ANSI-99 SQL support
  • Distributed pessimistic, optimistic and deadlock-free ACID transaction support
  • Sits in-between SQL-based applications and RDBMSs, eliminating the need to replace SQL with code
  • Native integration with RDBMSs, NoSQL databases and Hadoop
  • Distributed in-memory database with better scalability, availability and reliability
  • Cross-language support for Massively Parallel Processing (MPP) for Java, .NET and C++
  • Support for Apache® Spark DataFrames, RDDs, HDFS and SparkSQL acceleration
  • Built-in Continuous Learning Framework with support for machine learning and deep learning
  • Built on Apache® Ignite, a top 5 Apache Software Foundation project based on commits and list activity

Detailed GridGain and Terracotta Feature Comparison

This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Terracotta compare in 25 different categories including:

  • 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

Feature GridGain PE 2.5
Apache Ignite 2.5
GridGain EE 8.5 GridGain UE 8.5 Terracotta 4.3.5
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)
(Terracoptta DB offers disk-based persistance and separate EHCache instance)
Web Session Clustering
Apache Spark Acceleration  
Hadoop Acceleration  
In-Memory File System (Hadoop Compliant)  
Third Party Database Support, Persistence
Automatic 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)
Automatic integration with Apache Cassandra  
Inline Support for MongoDB  
Write Through and Read Through
Write-Behind Caching
Auto-Loading of SQL Schema/Data
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