TimescaleDB is an open-source relational database for time-series data, built on top of PostgreSQL. It uses full SQL and is easy to use like a classic relational database, but is able to provide scaling and other features that are typically reserved for purpose-built NoSQL databases.
TimescaleDB databases can be integrated with a wide range of services and applications for data analysis and other purposes. It is very easy to import a TimescaleDB database into Clarify, providing a cost-efficient and simple way of getting value from the time series data collected from your IoT network.
Clarify makes it easy to visualize IoT time series data, access it on web and mobile devices, as well as sharing data to other people. With Clarify, your organization can focus on key business goals instead of configuring dashboards or developing expensive custom solutions.
TimescaleDB is developed by Timescale Inc, which was incorporated in 2015 by Ajay Kulkarni and Michael Freedman, two MIT graduates that wanted to develop a new database solution for storage of IoT data from potentially millions of devices in an easily analyzable manner.
The Timescale team decided to build on top of Postgres, a popular open-source SQL database, instead of developing a new database from scratch in order to make TimescaleDB a more reliable option.
According to Timescale founders, in 2021 TimescaleDB had more than 2 million monthly active databases.
The company is based in New York City, but operates as a remote organization, with 60 employees in 20 different countries around the world.
TimescaleDB was created as an all-in-one database solution for data-driven applications, providing users with a purpose-built time-series database combined with a classic relational (PostgreSQL) database with full SQL support.
Accelerated performance is one of the main distinctive features of TimescaleDB. According to the developers, this database is able to run queries 10 to 100 times faster compared to PostgreSQL, InfluxDB, and MongoDB. They also claim TimescaleDB supports up to 10 times faster inserts and is able to ingest more metrics per second per server for high-cardinality workloads.
The ability to handle massive amounts of data is another key feature of TimescaleDB as it was designed to effectively record and store IoT data. TimescaleDB allows users to store hundreds of billions of rows and dozens of terabytes of data per server. The database uses datatype‑specific compression, which allows it to increase storage capacity up to 16 times.
Another key advantage of TimescaleDB is the support of both relational and time-series databases, which allows users to simplify their technology stacks and store relational data alongside time‑series data.