Using TimescaleDB

TimescaleDB focuses on simplicity for our users and how they can operate and manage their database, infrastructure, and applications, especially at scale.

First and foremost, we developed TimescaleDB as an extension to PostgreSQL, rather than building a time-series database from scratch. We also chose not to introduce our own custom query language. Instead, TimescaleDB fully embraces SQL.

The most important design aspect for providing users with a simple interface to the database is the TimescaleDB hypertable, explained in our database architecture section.

Essentially, hypertables abstract away the complexity of TimescaleDB’s automatic partitioning, so users don’t have to worry about managing any of the underlying chunks individually. Instead, users can focus on developing and interacting with their data as they would with regular tables within a PostgreSQL database. For advanced users, TimescaleDB is transparent about the presence of chunks and allows several ways to access them directly. This section covers all of the operations, and more, for using TimescaleDB.

Write clustering for multi-node TimescaleDB deployments is now available with TimescaleDB 2.0. Read more about or join our #multinode channel in our community Slack

That being said, workloads that may require a multi-node deployment on NoSQL databases can often be handled by a single TimescaleDB instance with one or more read replicas. The power of using a relational database to handle production-level time series data is discussed in further detail in this .

If you’re entirely new to SQL, here are some resources to help you get started:

• Khan Academy: Intro to SQL