VMware

VMware vFabric SQLFire is an in-memory distributed SQL database. In the category of NewSQL databases, SQLFire delivers dynamic scalability and high performance for data-intensive modern applications.

  • Speed; 30x faster than Oracle 11g*
  • Simple scale-out
  • Standard SQL

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Features

Operate at memory speed

Unlike disk-based data systems, vFabric SQLFire manages data in-memory   optimized for low latency and high performance.

Parallel, data-aware stored procedures

  • SQLFire enables applications to execute stored procedures in the database to move data-intensive logic close to where that data resides.  SQLFire enables an application to execute stored procedures on specific data nodes or in parallel on all the nodes of a server group.

Optionally write to disk

  • Data can be written to disk in parallel across the cluster as a function of the “shared nothing” architecture supporting recovery operations.
  • Each member node can persist data in disk files independently of other members. Failures in disks or cache failures in one node do not affect other instances being able to safely operate on their disk files.

Dynamically grow or decrease cluster size

  • Elasticity means vFabric SQLFire servers can dynamically come and go to serve a growing or shrinking demand pattern.
  • Continuous availability.
  • SQLFire enables you to replicate or partition any table while maintaining one or more redundant copies.

Leverage existing SQL knowledge to accelerate application development

Connect vFabric SQLFire clusters across geographically disperse areas via Wide Area Network (WAN) connections.

Continuous Availability

  • SQLFire enables you to replicate or partition any table while maintaining one or more redundant copies.
  • Data changes can be replicated asynchronously and in batch to one or more remote clusters for disaster recovery.
  • Active-active clustering across WAN is supported. This means that application clients can read and write to either cluster, and can also fail over to either cluster.

*VMware Internal Study, April 2012. Results available upon request.

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