TimescaleDB Overview

TimescaleDB is an open-source time-series database optimized for fast ingest and complex queries. It speaks “full SQL” and is correspondingly easy to use like a traditional relational database, yet scales in ways previously reserved for NoSQL databases.

Compared to the trade-offs demanded by these two alternatives (relational vs. NoSQL), TimescaleDB offers the best of both worlds for time-series data:

Easy to Use

Full SQL interface for all SQL natively supported by PostgreSQL (including secondary indexes, non-time based aggregates, sub-queries, JOINs, window functions).
Connects to any client or tool that speaks PostgreSQL, no changes needed.
Time-oriented features, API functions, and optimizations.
Robust support for Data retention policies.

Scalable

Transparent time/space partitioning for both scaling up (single node) and scaling out (forthcoming).
High data write rates (including batched commits, in-memory indexes, transactional support, support for data backfill).
Right-sized chunks (two-dimensional data partitions) on single nodes to ensure fast ingest even at large data sizes.
Parallelized operations across chunks and servers.

Reliable

Engineered up from PostgreSQL, packaged as an extension.
Proven foundations benefiting from 20+ years of PostgreSQL research (including streaming replication, backups).
Flexible management options (compatible with existing PostgreSQL ecosystem and tooling).

The rest of this section describes the design and motivation around the TimescaleDB architecture, including why time-series data is different, and how we leverage its characteristics when building TimescaleDB.

Next: In part to understand TimescaleDB’s design choices, let us ask: What is time-series data?

Download the Guide

If you want a quick visual intro to TimescaleDB, click on the image below to download the starter guide.