Newsletter
Timescale Newsletter Roundup: December 2021
Following the holiday’s spirit, we’re bringing you a (very cloudy) present: two new features in Timescale Cloud ☁️🎁, Promscale 0.7 new release, latest episodes from our Timescale Twitch Shows 📺, a new Developer Q&A, and a list of events we participated in.
General
Timescale flies when you’re having fun: 2021 in review
We're celebrating the accomplishments that made us proud in 2021 - like the advances in Timescale Cloud and TimescaleDB, new hyperfunctions, function pipelines, the support for OpenTelemetry in Promscale, and the many other launches from the year.
Docs
Want to learn how to use TimescaleDB?
Visit our comprehensive docs with API reference, user guides, tutorials, and much more.
Always Be Launching
Massive scale for time-series workloads: Introducing continuous aggregates for distributed hypertables in TimescaleDB 2.5
With this release, we introduce continuous aggregates in multi-node TimescaleDB, support for Postgres 14, and support for time zones in time_bucket_ng (under experimental).
Blog
What is ClickHouse, how does it compare to PostgreSQL and TimescaleDB, and how does it perform for time-series data?
An in-depth look at how ClickHouse and TimescaleDB architectures impact application design, developer experience, and performance - with detailed benchmark results comparing ingest speeds, disk space, and query response times.
Always Be Launching
Function pipelines: Building functional programming into PostgreSQL using custom operators
Today we are releasing function pipelines, a new feature that allows you to analyze data by composing multiple functions in SQL - introducing a simpler, cleaner way of expressing complex logic in PostgreSQL.
Blog
PostgreSQL vs Python for data evaluation: what, why, and how
Get a primer on using TimescaleDB and PostgreSQL to more efficiently perform your data evaluation tasks - previously done in Excel, R, or Python. Complete with short SQL refresher section, along with 1-to-1 code snippets comparing TimescaleDB and PostgreSQL code against Python code.
Blog
AWS Lambda for beginners: overcoming the most common challenges
Learn how to overcome three common challenges while building data pipelines with AWS Lambda. Add external dependencies to your Lambda function with Layers, overcome the 250MB package limit with Docker, and set up continuous deployment with GitHub Actions.
PostgreSQL
How percentile approximation works (and why it's more useful than averages)
Get a primer on percentile approximations, why they're useful for analyzing large time-series data sets, and how we created the percentile approximation hyperfunctions to be efficient to compute, parallelizable, and useful with continuous aggregates and other advanced TimescaleDB features.