TimescaleDB in 2024: Making Postgres Faster

If I had to summarize 2024 for Timescale, I’d call it the year of Postgres for AI. From game-changing open-source launches like ) to is a PostgreSQL extension for high-performance real-time analytics on time series and event data. It is available as an .

I love TimescaleDB (I was a user well before I worked at Timescale ❤️), so in the spirit of sharing that love, here are my top five TimescaleDB features from 2024 and why you should care (or at least why I do 😅).

1. Chunk-Skipping Indexes on Compressed Hypertables

This feature introduces a way to add min/max indexes on compressed

2. Faster Real-Time Continuous Aggregates and Continuous Aggregate Policies

allow the computation of results for newly inserted data on the fly (before the background job has materialized). That data is then immediately contained in queries to the continuous aggregate alongside the already materialized data to give a full, up-to-date snapshot.

In Timescale 2.14.0, we made a change that increased the performance of real-time continuous aggregates by up to for a quick how-to.

Faster continuous aggregate policies

In the past, continuous aggregates could sometimes be a little I/O hungry when updates flowed in for older chunks. Before version 2.17.0, we would recalculate and rewrite each chunk with changes, but now we use an efficient merge policy to only write the changes to storage. Overall, continuous aggregate policies are lighter, use fewer system resources in the background, and complete faster.

For anyone building dashboards or running real-time analytics with late-arriving data, this is a game-changer.

3. Hypercore Introduction and Enhancements

We’ve had a hybrid row-columnar storage engine for a long time (it powers our compression), but this year we gave it an official name: : Up to 500x faster updates and deletes by avoiding the need to decompress and materialize irrelevant batches.