Timescale Newsletter Roundup: September 2021

Timescale Newsletter Roundup: 
September 2021

In this edition, weโ€™re sharing a new developer story from our friends at Messari, ways to speed up your data analysis, new assorted tutorials, virtual events, and how-to guides to help you continue your journey to PostgreSQL and time-series data mastery ๐ŸŽ‰.

Weโ€™re on a mission to teach the world about time-series data, supporting and growing communities around the world. And, sharing educational resources as broadly as possible is one way to do just that :).

Hereโ€™s a snapshot of the content we shared with our readers this month (subscribe to get updates straight to your inbox).

Product updates & announcements

[Product Update]: New storage autoscaling on Timescale Cloud

We recently shipped storage autoscaling, a new feature to auto-increase database storage and keep operations running smoothly. (You can also set limits to control costs.)

New technical content, videos & tutorials

[Tutorial]: TimescaleDB with AWS Lambda

Weโ€™ve got a new tutorial for you to try your hand working with AWS Lambda and TimescaleDB! Follow our step-by-step instructions on how to create a data API for TimescaleDB (AWS Lambda + API Gateway), and how to pull data from 3rd party API and ingest it into TimescaleDB (AWS Lambda + Docker).

[Quick Start]: C# .NET and TimescaleDB

Weยดve recently added a new quick start guide to Timescale docs โ€“ designed to get the .NET developer up and running with TimescaleDB as their database. In this quick start guide, follow step-by-step instructions on how to connect, read, and write to a TimescaleDB instance from your .NET application.

[Watchlist]: Wrapping TimescaleDB functions for the Ruby ecosystem - part 1

In this video, Developer Advocate Jonatas Paganini navigates a minimal ActiveRecord example and discusses how to approach TimescaleDB functions along with migration files. At the end of the video, he ends up hacking the `create_table` method to also allow hypertable options.

[Watchlist]: Exploring NFL play-by-play data with TimescaleDB - part 2

Miranda Auhl continues to explore and analyze NFL data in her latest livestream, including tackling more complex queries with TimescaleDB continuous aggregates and hyperfunctions.

  • ๐Ÿ‘‰ Read the blog post to learn how to analyze 18M+ rows of NFL player performance data with PostgreSQL.
  • ๐Ÿ”Ž Explore the tutorial to get the NFL dataset and step-by-step guidance for ingesting, analyzing, and visualizing the data.
  • ๐Ÿฏ Follow us on Twitch to replay sessions and tune in whenever we go live.

[Watchlist]: TimescaleDB compression in PostgreSQL

Watch Ryan Boozโ€™s demonstration on how TimescaleDB compression works, how the hybrid storage technique allows you to speed up queries while saving more time-series data, and how to configure compression for your use case correctly.

New #remote-friendly events & community

[Community Spotlight]: How Messari uses data to open the cryptoeconomy to everyone

Learn how Messari sets up their data stack to collect, calculate, and contextualize crypto metrics, break down data silos, and bring transparency to the cryptoeconomy.

  • ๐Ÿ‘‰ Read the blog post.
  • ๐Ÿ™ Big thank you and shout out to our friends at Messari for sharing their story!

[Virtual Event]: Write the Docs Prague (October 3-5)

Join Timescale Documentation Manager Lana Brindley at Write the Docs Prague online this October. Lana will be sharing her experience with assessing docs information architecture, identifying required information architecture, and then implementing it for improving docs traffic performance.

[Virtual Meetup]: Timescale monthly Office Hours (October 5)

Join us โ€“ and fellow TimescaleDB community members โ€“ on Tuesday, October 5th for our next monthly Office Hours. Catch up on the latest product updates and upcoming releases, watch demos, meet community members, and ask any questions you have for our engineers.

TimescaleDB tips, reading list & more

How percentile approximation works (and why it's more useful than averages)

In his latest blog post, David Kohn explains what percentile approximations are, why they're useful for analyzing large time-series datasets, and how we created the percentile approximation hyperfunctions to be efficient to compute, parallelizable, and useful with continuous aggregates and other advanced TimescaleDB features.

AWS Lambda for beginners: overcoming the most common challenges

Learn how to solve the most common challenges - adding external dependencies, overcoming the 250MB package limit, and continuous deployment - while building time-series data pipelines with AWS Lambda. The solutions include Lambda Layers, deploying Docker image as a function, Github Actions, and TimescaleDB.

Speed up data analysis with TimescaleDB and PostgreSQL

Learn how TimescaleDB and PostgreSQL make data analysis fast, efficient, and easily accessible. Miranda breaks down why Excel, R, and Python arenโ€™t necessarily the best tools for all data munging tasks, ways to simplify how you store and access data, and much more.

How to build your own monitoring & alerting solution

Grafana is known for visualizations, but itโ€™s a powerful alerting tool too. Learn how to combine TimescaleDB, Grafana, and 5+ notification channels to define and trigger custom alerts for the metrics you care about.

How to create (lots!) of sample time-series data with PostgreSQL generate_series()

Generating sample time-series data with the PostgreSQL generate_series() function is a useful skill to have when evaluating new database features, creating demos, or testing insert and query patterns. Get the basics of what PostgreSQL generate_series() is and how to use it for your data generation needs.

Save time with PostgreSQL cheat sheet

Weโ€™ve rounded up essential psql commands in one easy-to-navigate place, so you spend more time querying your data, not trying to remember that command that always escapes you. Click, copy, done โœ….

โœจ Last week in #remoting-bonding fun: Our design team hosted a mini-design challenge - to draw your dream pizza ๐Ÿ•

Wrapping Up

And, lastly, if you know someone who'd like to join our team โ€“ or learn more about life on Team Timescale ๐Ÿฏ โ€“ we're currently hiring across all teams (and 100% remote). Check out our careers page to view all of our open positions.

Thanks!

The Timescale Team

๐Ÿ“† To see past issues of this newsletter, check out our archives.

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