Timescale Newsletter Roundup: March 2021 Edition

Timescale Newsletter Roundup: March 2021 Edition

In this edition, weโ€™re sharing the State of PostgreSQL 2021 survey (we'd love your feedback!), new Timescale Forge features, #TimescaleTuesday videos, and the latest developer Q & A from our friends at Everactive. We round out the post with a few of our favorite PostgreSQL and time-series resources, plus awesome technical content from community members.

Weโ€™re always releasing new features, creating new 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 new pieces in our biweekly newsletter.

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 ๐Ÿ™‚.

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

We just launched the second annual State of PostgreSQL survey to collect and share how developers across the globe use PostgreSQL to do amazing things โ€“ and we'd love to hear about YOUR experiences. Over the coming weeks, we'll publish key findings + full anonymized source data for everyone in the Postgres community to download and explore โœจ.

State of PostgreSQL 2021 Survey graphic with shortlink
Take the State of PostgreSQL 2021 survey! The survey is open until April 16th at 11:59pm PT.

We recently shipped some ๐Ÿ’ฏ Timescale Forge features, including the ability to scale up to 4TB instances, set custom maintenance windows, and use "Timescale Forge Explorer" for an at-a-glance view of database policies, compression ratios, and more.

Our engineering team shares how weโ€™ve designed Promscale to make it easy to collect, store, and perform complex analysis on your Prometheus metrics. Our goal is to let you ask any question, build any dashboard, and focus on finding *answers* in your metric data.

New technical content, videos & tutorials

Learn how to use two of @RyanBooz' favorite analytical functions to answer time-series questions like "What was the MIN/MAX value in a bucket?", "What time did that reading occur?", and more.

In this SQL-packed video, @RyanBooz breaks down how - and why - to use TimescaleDB 2.0 informational views and functions to get details about your chunks and hypertables.

@RyanBooz's new #TimescaleTuesday video series focuses on tackling community member questions, and in this installment, he covers how Continuous Aggregates handle refresh policies. Youโ€™ll get his tips for ensuring your refresh policies and windows align and materialize the data you expect.

Time-series data and visualizations go hand-in-hand, and this step-by-step tutorial takes you through how to get up and running with TimescaleDB and Tableau in 3 steps. Youโ€™ll connect your database, see how to run queries from within Tableau, and visualize your results.

New #remote-friendly events & community

Learn how our friends @Everactive set up a data stack to bring IoT analytics and real-time monitoring to places never before possible, plus their advice, database evaluation criteria (they went all-in on Postgres, switching from OpenTSDB ๐Ÿ”ฅ), and more.

Sign up to chat with our product & engineering team, ask questions, and meet fellow community members. You can submit questions in advance or simply join to listen in โ€“ everyone is welcome!

Our public Slack community is a place to ask questions, share best practices, and get the latest updates โ€“ and weโ€™re always humbled to see members share what they're working on and jump in to help others.

  • ๐Ÿ‘‹ Havenโ€™t checked it out yet? Join TimescaleDB Slack community (anyone and everyone is welcome).
  • ๐Ÿ’ฌ You'll find fellow community members, Timescale engineers & our co-founders active in all channels.

TimescaleDB tips, reading list & more

Follow this detailed tutorial to learn how to analyze your data and make predictions. You'll use a real dataset and run sample queries for not one, but two forecasting approaches: ARIMA and Holt-Winters.

Timescaledb-tune helps you ensure you set up and configure an instance thatโ€™s optimized for your environment, while timescaledb-parallel-copy helps you run concurrent COPY commands to improve your insert rate. Fun fact: theyโ€™re both written in Go ๐ŸŽ‰.

@avthars covers two ways to store and query time-series data in MongoDB โ€“ and how TimescaleDB stacks up against MongoDB across several dimensions. In a nutshell, TimescaleDB outperforms both MongoDB methods (by a lot - up to 250%+ higher insert performance and 54x faster queries) and requires much less code and time to implement.

Get Mike (Timescale CTO and co-founder)โ€™s top ways to speed up INSERTs, from optimizing disk performance to using parallel writes and batch inserts. He includes tips for vanilla Postgres and a few TimescaleDB-specific ones ๐ŸŽ‰.

Grafana might be best known for visualizations, but itโ€™s a powerful alerting tool too. @Avthars shows you how to define 3 alert rules and send notifications through channels like Slack, PagerDuty, and OpsGenie. You'll get step-by-step demos and best practices for creating custom alerts for the metrics that matter to you.

Get quick tips for using your SQL skills for time-series data analysis, from technical guidance to our favorite tools. ๐Ÿ™Œ

In the world of databases, cardinality refers to the number of unique values contained in a particular column, or field, of a database. However, with time-series data, things get a bit more complex. Our engineers cover what causes high-cardinality, how it looks in the real world, and different time-series databases handle this โ€œproblem.โ€

Learn how @nick_jastix set up a ๐Ÿ”ฅ data stack to to analyze Twitch channel trends, complete with how they extracted and prepared Twitch API data, their analysis and key findings, and how TimescaleDB stacked up to other options.

  • ๐Ÿ™ Big thank you to Nikolay for sharing!
Tweet from Nikolay with SQL code data analysis

What can we do to provide better request handling and access times? Read this shot how-to to get a primer on time-series data and integrating Elixir and Ecto with TimescaleDB and in just a few steps.

We're continually amazed at the ways engineers use time-series data (and TimescaleDB) to solve problems โ€“ and farmfol.io is no exception. ๐Ÿ’› Thank you to @iam4x for sharing!

Wrapping Up

And, that concludes this monthโ€™s newsletter roundup. Weโ€™ll continue to release new content, events, and more - posting monthly updates for everyone.

If youโ€™d like to get updates as soon as theyโ€™re available, subscribe to our newsletter (2x monthly emails, prepared with ๐Ÿ’› and no fluff or jargon, promise).

Happy building!

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