MemSQL has made available a distributed version of its in-memory database and real-time analytics platform, enabling organizations to perform real-time analytics at big data scale. Also included in ...

Your business is finally starting to grow and your cache size has morphed into a distributed in-memory database requiring the added burden of sharding, clustering, and other new techniques.

Database vendors are responding to growing enterprise requirements for real-time access to stored data. The Terracotta database runs on top of a distributed in-memory data grid dubbed BigMemory, which ...

Among them was the chance to review NoSQL and in-memory databases. The team opted to work with Redis Labs to build the distributed, in-memory key-value database into the caching system.

As to the platform’s architecture, GridGain is JVM-based distributed middleware software. See the full white paper for key features, including in-memory data grid, in-memory database, in-memory ...

More databases and data stores and the applications that run atop them are moving to in-memory processing, and sometimes the memory capacity in a single ...

MemSQL, which specializes in real-time databases for transactions and analytics, has announced new geospatial capabilities for its in-memory, distributed SQL-based database. By bringing together ...

MemSQL announced Sept. 18 that its distributed in-memory database, which competes with similar DBs from SAP, SAS, Teradata, Oracle, Birst and several others, has become the first to provide Java ...

Spark is a Big Data analytics platform that leverages both data in memory and data on disk across a distributed cluster with the objective of aggressively maintaining data in memory.

However, many in-memory data grids require that all the data in the underlying disk-based database fit into memory, requiring a business to purchase enough memory to hold all the data.