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InfoQ Homepage News MemSQL 4 Database Supports Community Edition, Geospatial Intelligence and Spark Integration

MemSQL 4 Database Supports Community Edition, Geospatial Intelligence and Spark Integration

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Latest version of MemSQL, in-memory database with support for transactions and analytics, includes a new Community Edition for free use by organizations. This edition supports real-time in-memory data processing for different data formats like relational, JSON, and geospatial data. MemSQL 4, released last week, also supports integration with Apache Spark, Hadoop Distributed File System (HDFS), and Amazon S3.

The database solution can be used to capture and analyze both real-time and historical data more efficiently and also to improve business performance in areas such as the Internet of Things, financial services and mobile applications. The main features in the new release are the real-time geospatial data analytics and integration with Hadoop and Spark.

Real-Time Geospatial Intelligence: MemSQL 4 natively supports geospatial data and analytic functions so the users can create geo-aware mobile apps and perform real-time analytics for objects on the move. As part of its work with GIS mapping organization Esri, MemSQL offers the real-time geospatial capabilities that enable enterprises to visualize geolocation based data intelligence. This feature allows the users to store geospatial and operational data in the same database. MemSQL integrates geospatial data as a primary data type, making it as easy to use and operate as any other type of data.

Spark and Hadoop Integration: MemSQL 4 has integration with big data processing frameworks like Apache Spark, Hadoop Distributed File System (HDFS), and Amazon S3, so any organization can get real-time insights from its data. MemSQL Spark Connector can be used to operationalize Apache Spark and perform real-time insights on the data stored in HDFS or S3 distributed data stores. By integrating Spark and MemSQL technologies, users can load data in parallel between MemSQL and Spark clusters, deploy models using an operational data store, and serve results of analytics via a SQL interface.

Other new features in MemSQL 4 release include an enhanced optimizer and expanded SQL functionality. There is also an updated disk-based column store coupled with an in-memory row store that provides more flexibility in storing and managing the enterprise data.

MemSQL 4 Community Edition can be downloaded from their website. You can also launch a MemSQL database cluster on Amazon EC2 using Amazon CloudFormation to automatically provision and configure the MemSQL cluster.


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