Timescale Newsletter Roundup: March 2021 Edition
In this edition, we’re sharing the State of PostgreSQL 2021 survey (we'd love your feedback!), new Timescale Cloud 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.
We’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.
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 & announcementsState of PostgreSQL 2021 survey is now open!
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 – 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 ✨.
- 📥 Start the survey ~30 questions, estimated 10-15 mins to complete.
- 🐘 Help us spread the word! We’re keen to get a representative and diverse mix of perspectives, so please share with anyone who may be interested.
- 🔎 Check out the State of PostgreSQL 2019 survey findings.
We recently shipped some 💯 Timescale Cloud features, including the ability to scale up to 4TB instances, set custom maintenance windows, and use "Timescale Cloud Explorer" for an at-a-glance view of database policies, compression ratios, and more.
- 🚀 Check out our Timescale Cloud 101 playlist for demos and a quick tour of what's new.
- 🔭 See our Timescale Cloud docs for more details.
- ✨ Log-in to your account or start a free trial at any time to start exploring.
Our engineering team shares how we’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.
- 🔎 Check out our GitHub README to get started.
- 📅 Attend our next Promscale User & Community meeting on Wednesday, May 12th.
- 🙋 Have feedback or questions? Let us know on Slack (#Promscale channel).
New technical content, videos & tutorialsFun with SQL analytical functions - Part I: First() and Last()
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.
- 🔎 Check out our Advanced Analytics docs for additional functions.
- 🧐 Learn how and why we’re building Timescale Analytics: one-stop shop for time-series analytics in PostgreSQL.
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.
- 🎥 Explore the full #TimescaleTuesday playlist for more tips and technical demos.
- ➕ Subscribe to #TimescaleTuesday to follow along each week.
@RyanBooz's new #TimescaleTuesday video series focuses on tackling community member questions, and in this installment, he covers how Continuous Aggregates handle refresh policies. You’ll get his tips for ensuring your refresh policies and windows align and materialize the data you expect.
- 🔎 Check out our continuous aggregates docs for more guidance, sample queries, and advanced scenarios.
- 🔧 Review our Changes in TimescaleDB 2.0 guide for more about what's new.
- 🎥 Explore the full #TimescaleTuesday playlist to get more helpful tips and technical demos for TimescaleDB.
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. You’ll connect your database, see how to run queries from within Tableau, and visualize your results.
- 💻 Want more step-by-step guides? Browse all of our tutorials (20+).
New #remote-friendly events & communityHow Everactive powers a dense sensor network with virtually no power at all
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 🔥), and more.
- 🙏 Huge shoutout and thank you to Dan Wright and Clayton Yochum at Everactive.
- 👉 Learn more about Everactive.
- 📣 Want to share your story? Email firstname.lastname@example.org and we’ll make it happen.
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 – everyone is welcome!
- 📅 Reserve your spot.
- 💬 If you can’t join, but have a question, reach out to our engineering team on Slack.
Our public Slack community is a place to ask questions, share best practices, and get the latest updates – and we’re always humbled to see members share what they're working on and jump in to help others.
- 👋 Haven’t checked it out yet? Join TimescaleDB Slack community (anyone and everyone is welcome).
- 💬 You'll find fellow community members, Timescale engineers & our co-founders active in all channels.
TimescaleDB tips, reading list & moreBuild time-series forecasting models with R, Apache MADlib & Python
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.
- ✈️ Read how FlightAware combines TimescaleDB and Grafana to track their flight prediction model performance over time.
Timescaledb-tune helps you ensure you set up and configure an instance that’s optimized for your environment, while timescaledb-parallel-copy helps you run concurrent
COPY commands to improve your insert rate. Fun fact: they’re both written in Go 🎉.
- 📖 Read this classic blog post to learn more about how and why we built timescaledb-tune.
- ⚙️ Find timescaledb-tune on GitHub.
- 👀 Find timescaledb-parallel-copy on GitHub.
@avthars covers two ways to store and query time-series data in MongoDB – 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.
- 📈 Check out the Time Series Benchmarking Suite to re-run the benchmarks yourself & compare other time-series databases.
Get Mike (Timescale CTO and co-founder)’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 🎉.
- 🍿 Watch @avthars technical session to learn about factors that impact PostgreSQL ingest rate and see 5 of Mike's tips in action.
- ⚡ Use timescaledb-parallel-copy to bulk insert large amounts of data quick-start.
Grafana might be best known for visualizations, but it’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.4 ways to use SQL for time-series data
Get quick tips for using your SQL skills for time-series data analysis, from technical guidance to our favorite tools. 🙌What is high cardinality, and how do time-series databases like InfluxDB and TimescaleDB compare?
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 “problem.”Rill Treasure Hunt: CIS Twitch Oscar 2020
Learn how @nick_jastix set up a 🔥 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.
- 🙏 Big thank you to Nikolay for sharing!
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.
- 🙏 Shout out to @BartoszGorka96 for such an awesome post!
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).