Merging the Key Elements of a Seamless Converged Data Platform

According to 451 Research, a converged data platform includes:

  • Distributed Grid/Cache
  • Stream Processing
  • Relational Operational Database
  • NoSQL Database
  • Hadoop
  • Analytic Database
  • Containerization

The GridGain® in-memory computing platform includes all of the elements of a converged data platform including an in-memory data grid, a relational, operational in-memory database, in-memory streaming analytics, plus a continuous learning framework for machine and deep learning. GridGain seamlessly integrates with relational operational databases (RDBMS), NoSQL databases, and with Hadoop while offering ACID transactions, ANSI-99 SQL, query processing acceleration, and massive scalability. Once data is uploaded into GridGain, analytics at in-memory speeds can be run on the data in the GridGain cluster. GridGain is easily containerized using solutions such as Docker or Kubernetes for ease of deployment.

Learn more about the emergence of the converged data platform by watching our webinar with Matt Aslett of 451 Research entitled "The Emergence of Converged Data Platforms and the Role of In-Memory Computing".