| TimescaleDB Production Ready |
| Written by Kay Ewbank | |||
| Thursday, 08 November 2018 | |||
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TimescaleDB, an open-source PostgreSQL extension for time-series that is optimized for fast ingest and complex queries, has been released as production ready by its developers. TimescaleDB has already been downloaded over a million times, and there are production deployments at Comcast, Bloomberg, and Cray. This 1.0 release offers native Grafana integration and Prometheus support. TimescaleDB supports full SQL and is designed to scale well. The developers say it can ingest millions of data points per second; scales tables to 100s of billions of rows and 10s of terabytes; and when used for time-series data is much faster than InfluxDB, Cassandra, MongoDB, and vanilla PostgreSQL. In addition to Grafana and Prometheus, TimescaleDB supports Tableau, Apache Kafka, Apache Spark, and Zabbix. Features designed for managing time-series data include automatic space-time partitioning, a hypertable abstraction layer, and adaptive chunk sizing. It also supports geospatial analysis and JSON format data. Improvements in this release over the earlier release candidate include easier to use time-series manipulation functions, including an explicit arbitrary datetime with which to start time bucketing for common aggregation functions (e.g., September 1), as well as aligning weeks starting from Monday to respect the ISO standard. Management of multiple tablespaces has also been improved to allow hypertables to elastically grow across many disks, and there's more information available about the state of hypertables, their dimensions, and their chunks when creating and managing data. This release also improves the foundation for a database scheduling framework that manages background jobs. This will be used in future releases to add more automation around areas such as automatic data aggregation, retention, and archiving. The native support for Grafana includes a new visual query editor for the PostgreSQL/TimescaleDB datasource, so that users don’t have to write SQL to access their data. Both the query editor and the underlying PostgreSQL datasource have been written by TimescaleDB developers as part of Grafana's open source code.
More InformationRelated ArticlesOpen Source Time Series Database Released PostgreSQL Improves Declarative Partitioning PostgreSQL Adds Parallel Query Support PostgreSQL Plus Cloud Database
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