Timescale Newsletter Roundup: September 2020 Edition
See what's new from Team Timescale, including big news about the Timescale License - updated to give more rights to our users, enterprise features 100% free, and more! - TimescaleDB 2.0 beta releases, new technical content, and PostgreSQL pro tips 🚀.
We’re always releasing new features, creating documentation and tutorials, and hosting virtual sessions to help developers do amazing things with their data. And, to make it easy for our community members to discover and get the resources they need to power their projects, teams, or business with analytics, we round up our favorite pieces in our biweekly newsletter.
We’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 :).
Here’s a snapshot of the content we shared with our readers this month (subscribe to get updates straight to your inbox).
Product updates & announcements
We just announced updates to our Timescale License - which governs some of our most advanced features, like compression, continuous aggregates, and multi-node - to provide expanded rights to all of our users (YOU!). Ajay and Mike detail how we’ve taken your feedback to heart and liberalized our software license – and why we think all open-source businesses should adopt a similar model.
- 📰 See the resulting Hacker News discussion (200+ comments).
- 🙋 Have feedback or questions? Let us know on Slack.
[Product Update #1]: TimescaleDB 2.0 Beta-6 >>
We’re working toward a TimescaleDB 2.0 Release Candidate, and our latest beta version focuses on TimescaleDB capabilities related to single-node operation, including updated APIs for continuous aggregates (greater control!), user-defined jobs, and better informational views.
- 🚀 Get installation instructions and details about what’s new.
- 💬 See our Public Slack announcement for a summary of changes and resources.
[Product Update #2]: TimescaleDB 1.7.4 >>
We released two maintenance releases in short order: 1.7.3, which fixes issues in a few core capabilities: drop_chunks (data retention policies), compression, and the background worker scheduler, and 1.7.4, which fixes an issue for users who’ve deployed TimescaleDB replicas.
New technical content, videos & tutorials
[Session Replay]: Postgres Pro Tips Part II: 5 Powerful PostgreSQL Functions for Monitoring & Analytics >>
In yet another demo-packed session, @avthars shows you how to build queries for common DevOps scenarios, including things like calculating averages and deltas, addressing missing data, and more.
- 🔥 Get the sample app and demo dataset (Python script)
- 🏆 Check out 10+ advanced analytics functions (TimescaleDB docs)
[Postgres Pro Tips]: Top 5 5 PostgreSQL Extensions >>
We love PostgreSQL for many reasons, but a big one is its extensibility and vast ecosystem of 20K+ extensions. We round up a few of favorites, why you’d use and how to install each one, plus a few sample queries and pro tips to get you started.
- 🔎 See @avthars Twitter thread for an at-a-glance breakdown (and chime in!).
- 🙏 Thank you to all of the TimescaleDB community members who recommended their favorites.
New #remote-friendly events & community
[IoT + Time-Series]: Combining the Power of IoT & Time-Series Data Session Replay >>
Learn how Team Grillo builds earthquake early warning systems - used all around the world to warn communities - and how to get involved in their new open source initiative: OpenEEW. From there, Mario breaks down what IIoT is and why it's unique, various data models, and when and why to use each type.
- 🙏 to our guest speakers: Andy Meira (Grillo Founder) and Mario Ishikawa (PackIOT CTO & Timescale Hero)
[Community Spotlight] How k6 delivers high-performance load testing >>
Kudos to our friends at k6 for their work to build resilient, reliable load and performance testing for developers everywhere. See how they’ve designed their data stack to support their ever-growing customer base and massive amounts of time-series data, now and in the future.
[Community Q & A]: Join us for Office Hours on Tues, October 6th >>
Our monthly Office Hours series continues! Anyone and everyone is welcome, whether you’re new to TimescaleDB, an experienced database pro, or somewhere in the middle – our technical team is happy to answer any and all questions.
- 👉 Reserve your spot on Tuesday, Oct 6th (space is limited).
- 💬 If you can’t join, but have a question, reach out to our engineering team on Slack.
TimescaleDB tips, reading list & etc.
[TimescaleDB Tip #1]: Connect your Tableau data in just a few clicks >>
Check out this tutorial to get up and running in 3 steps. You’ll connect to your TimescaleDB database, then get sample SQL queries and advice for examining time-series data.
[TimescaleDB Tip #2]: Get up and running with schema design best practices >>
The right PostgreSQL table schema can be the difference between significant performance improvements and significant performance degradation. Use this guide to get detailed best practices and examples to create the best indexes, triggers, and constraints for your projects.
[Reading List]: A tuned database means better read and write performance* >>
We built timescale-tune to help you get the best configuration for your unique setup, and, in this classic post, we share what is, how it works, and how to put it to use.
- 🔧 Get timescale-tune on GitHub.
- 🏁 See our configuration docs for additional tips.
- *~1M metrics/second and 3x faster queries in our benchmark testing.
[Reading List]: Using SQL functions for time-series analysis >>
TimescaleDB is designed to handle advanced time-series workloads, including special SQL functions optimized for time-series analytics. Our product team shares how we built
gap_fill to solve the all-too-common problem of missing - or messy - data, how each one works, and where to get started.
[Time-Series Fun]: Compare database performance with the Time-Series Benchmarking Suite (TSBS) >>
Take the guesswork out of benchmarking: learn how to use TSBS to generate realistic real-world datasets that mimic production workloads and compare read + write performance across various time-series databases. This post gives step-by-step instructions for the IoT dataset and a few sample queries to inspire your own analysis.
- Get TSBS on GitHub - available for IoT and DevOps scenarios.
[Team Timescale Fun #1]: NEW Timescale Shop Stickers and Limited-Edition T-shirts >>
Timescale Shop is chock-full of classic Timescale swag and limited edition items, and we just released some fresh new designs featuring Eon, our adorable Tiger mascot.
- From sunglass-adorned Eon to showing support for #BLM and Pride, there’s something for everyone
- Something missing? Let us know and we’ll add it to our backlog.
[Team Timescale Fun #2]: Timescale People Manager Mel continues to dial up her async challenge game.
And, that concludes this month’s newsletter roundup. We’ll continue to release new content, events, and more - posting monthly updates for everyone.
If you’d like to get updates as soon as they’re available, subscribe to our newsletter (2x monthly emails, prepared with 💛 and no fluff or jargon, promise).