MemSQL 4.1 features the new MemSQL Streamliner and columnstore enhancements that simplifies the creation and management of real-time data pipelines running in Apache Spark.
Key features and improvements of MemSQL 4.1
- Faster streaming into columnstore tables
- Alter table for columnstore
Get Started with MemSQL Community Edition
Unlimited scale and capacity. Free forever.
MemSQL 4 is our latest major release. In addition to new features and improvements, MemSQL 4 introduces the MemSQL Community Edition - an operating mode of MemSQL with unlimited capacity that is free forever. This release also comes with a new cluster management tool and big data ecosystem connectors.
Key features and improvements of MemSQL 4
- Fully distributed JOINs
- Geospatial data types and functions
- Enhanced query optimizer
- Updated MemSQL Ops
MemSQL Spark Connector
We released the MemSQL Spark Connector, giving users the ability to read and write data between MemSQL and Apache Spark. MemSQL can easily handle the high rate of inserts and reads that Spark often requires, while also having enough space for all data that Spark can create.
The MemSQL Spark Connector comes with a number of optimizations, such as reading data out of MemSQL in parallel and making sure that Spark collocates the data in its cluster with MemSQL nodes as much as possible. It also provides two main components: a MemSQLRDD class for loading data from a MemSQL query and a saveToMemsql function for persisting results to a MemSQL table.
MemSQL 3.2 included key feature and performance enhancements including:
- Improved transaction capabilities through support for multi-statement transactions
- Significantly improved query performance against tables using a column store index through sorted segments and segment elimination
- Improved JOIN performance between tables using column store indexes through merge JOINs