Migrating from DataSynapse to GridGain and Modern In-Memory Computing
Since DataSynapse was purchased by TIBCO in 2009, the distributed computing market has been transformed by the development of in-memory computing to solve a host of performance and scalability challenges. The performance required for different stress scenarios and back-testing have increased by up to 50x. Existing high-performance computing and analytics infrastructure such as DataSynapse GridServer can’t deliver both the real-time speed and 100x (or greater) scale.
GridGain was founded 2009, and in 2014 donated the core code to the Apache Ignite in-memory computing project. Today, thousands of companies use Apache Ignite and GridGain (the commercially-supported version of Ignite) for in-memory computing. Most implementations use GridGain as a compute grid.
GridGain has the capabilities of DataSynapse, coupled with a host of other capabilities for a variety of in-memory computing use cases. Users can achieve a 1,000x increase in application performance while scaling out to petabytes of in-memory data across a cluster of commodity servers.
The combination makes it straightforward to migrate applications from DataSynapse GridServer to GridGain software, and also run most of the latest distributed computing workloads on the same in-memory computing platform.
This product comparison describes the advantages and benefits of migrating from DataSynapse to GridGain as an in-memory computing solution to power mission-critical and data-intensive applications.