Using TimescaleDB

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.

TimescaleDB supports all SQL operations and queries one would expect out of PostgreSQL. This includes how tables are created, altered and deleted, how schemas are built and indexed, and how data is inserted and queried. Additionally, TimescaleDB adds necessary and useful functions for operational ease-of-use and analytical flexibility. In general, if you are familiar with SQL, TimescaleDB will be familiar to you.

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.

Clustering

TimescaleDB also supports PostgreSQL’s built-in replication functionality for high availability, redundancy, and sharding read queries. Hypertables are fully compatible with the PostgreSQL streaming replication protocol, as explained in our streaming replication tutorial. Streaming replication setups can be further extended to offer high availability and failover using community tools like patroni.

Write clustering for multi-node TimescaleDB deployments is under active development, and we’re excited to share our progress with the community soon. 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 blog post.

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

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