MemSQL has introduced the MemSQL Spark Connector. According to the vendor, the combination of an in-memory database from MemSQL and Spark's memory optimized processing framework gives enterprises the benefit of fast access to transactions, ETL, and analytics. The MemSQL Spark Connector is also available as an open source offering, providing developers the ability to adapt it to their needs.
A purpose built database for instant access to real-time and historical data, MemSQL uses a SQL interface and a horizontally scalable distributed architecture that runs on commodity hardware or in the cloud.
The MemSQL Spark Connector utilizes the in-memory and distributed architectures of both MemSQL and Spark for high performance parallel throughput. With the MemSQL Spark Connector, operational data can be made immediately available for analysis in Spark, giving enterprises and data exploration teams access to real-time data. In addition, results from Spark operations can be quickly placed into production by transferring back to the MemSQL persistent and transactional database. The MemSQL Spark Connector utilizes the in-memory and distributed architectures of both MemSQL and Spark for high performance parallel throughput.
"Spark is an impressive execution engine for data exploration, and enterprises can now operationalize Spark results with persistent databases," said Eric Frenkiel, CEO and co-founder, MemSQL. "The integration between MemSQL and Spark represents the best of both worlds — giving enterprises an ability to automate data-driven decision making, perform real-time operational analytics and detect and respond to anomalies in real-time."
To download MemSQL Spark Connector, visit the MemSQL Github site.