Citus Data Releases New Version of CitusDB

SAN FRANCISCO, Calif., March 26 — Citus Data, creators of solutions to scale out and extend the analytics capabilities of PostgreSQL, today announced the general availability of CitusDB 4.0, the latest release of the company’s hybrid transaction/analytical processing platform for massively scalable, high availability PostgreSQL. CitusDB 4.0, based on the latest PostgreSQL 9.4 release, enables companies to massively scale out PostgreSQL across commodity servers and use parallel processing to distribute queries across the cluster for real-time analytics queries on big data. The CitusDB 4.0 release improves performance and usability while migrating to the PostgreSQL 9.4 platform, which provides greatly enhanced support for unstructured data types.

CitusDB 4.0

The advanced CitusDB platform powers hybrid transaction/analytical processing across hundreds of billions of events while cutting query times by up to 100x. By moving to PostgreSQL 9.4, the platform now provides enhanced support for both structured and unstructured data through JSONB. CitusDB 4.0 brings exciting new functionality and performance improvements, including:

• Support for real-time workloads for hybrid transaction/analytical processing – CitusDB Enterprise Edition now integrates with pg_shard to support real-time workloads. This integration combines scalable analytics and low-latency writes in a single system.
• Integration with PostgreSQL 9.4 – New features include JSONB support, a faster, more efficient data type for storing JSON data, faster and smaller GIN indexes, and more PostgreSQL 9.4 features.
• Ability to re-balance the cluster for incremental scalability and fault tolerance – Users can incrementally add nodes and uniformly distribute data, and thus traffic, to those nodes. Users can also re-replicate data from failed nodes evenly across all the remaining nodes.
• Faster query performance – A new task-assignment policy provides better in-memory workload performance, while binary serialization for data copied between nodes provides faster performance on queries fetching a lot of data. Batching task-assignment calls improves performance with re-partition joins.
• Improved usability – Modified \STAGE allows loading data from any node in the cluster, making data-loads much easier and allowing for a more uniform data placement. Query throttling in the real-time executor prevents resource exhaustion when queries touch thousands of shards.