Introducing the GridGain In-Memory Computing Platform


GridGain® is the leading in-memory computing platform for real-time business. It is the only enterprise-grade, commercially supported version of the Apache® Ignite™ open source project.

Many companies use GridGain as shared data and processing infrastructure across projects to deliver in-memory speed and unlimited scalability for transactions, analytics, hybrid transactional, and analytical processing (HTAP) and streaming analytics. GridGain provides speed and scale by sliding between existing application and data layers as an in-memory data grid (IMDG) with no rip-and-replace of the underlying database. GridGain enables companies to deliver high volume, low latency transactions and analytics. It also simplifies streaming and analytics by acting as a shared data store and compute engine with real-time stream ingestion, processing, streaming analytics, and continuous learning.

This white paper covers in-depth the architecture, key capabilities, and features of GridGain, and as well as its key integrations such as leading RDBMSs, Apache Spark™, Apache Cassandra™, MongoDB®, and Apache Hadoop™. You will learn how GridGain can add in-memory speed and unlimited horizontal scalability to your company’s existing or new OLTP or OLAP applications, new or existing HTAP applications, streaming analytics, and continuous learning use cases involving machine or deep learning with TensorFlow.