MemSQL’s cluster management platform’s new release features major improvements for using Spark and Python, and support for non-uniform memory architectures.
Real-time analytics database provider MemSQL has announced an update to their MemSQL Ops platform, a management console for MemSQL clusters.
In a Dec 16th release, the company said the latest version now supports Non-Uniform Memory Architectures (NUMAs) for automatic memory provision. It also allows web-based Python programming via the MemSQL Streamliner and improves the use of Spark with Spark SQL pushdowns. All of these improvements are intended to boost the platform’s speed and efficiency and provide fast analytics via real-time data pipelines.
Related: What’s behind the attraction to Apache Spark
Spark SQL pushdowns now provide the ability to combine the speed of MemSQL with Spark’s high performance. According to the company, SQL queries now run on Spark inside the MemSQL container, which can improve performance up to 50 times, and the platform now supports Spark 1.5. The web-based Python programming support allows coding to be performed within a browser, eliminating the need to compile a separate program.
Want more? Check out our most-read content:
Research from Gartner: Real-Time Analytics with the Internet of Things
The Value of Bringing Analytics to the Edge
Frontiers in Artificial Intelligence for the IoT: White Paper
Data Visualization: How a Futures Exchange Sees Clearly
John Bates, Plat.One: Enterprise IoT Doesn’t Have to Be Hard
Why Edge Computing Is Crucial for the IoT
Why Gateways and Controllers Are Critical for IoT Architecture
Liked this article? Share it with your colleagues!
