Timescale Newsletter Roundup: October 2021

Timescale Newsletter Roundup: 
October 2021

In this edition, we’re sharing tons of news - starting with the kick-off of #AlwaysBeLaunching, part two! 🥳

If you are new to Timescale, last May we set ourselves the ambitious (and slightly foolish) goal of doing 10+ launches in one month. And not only did we accomplish that goal - we did it again. The month of October 2021 was filled with #AlwaysBeLaunching new product updates and releases - 13 to be exact! Keep reading for more details!

We’ve had a couple of amazing weeks for Team Timescale. We announced the support for OpenTelemetry traces in Promscale 🎉 while having the chance to interact with many community members during the PromCon & KubeCon+CloudNativeCon North America! A huge thank you to everybody who stopped by our booth 🙏 it was an absolute pleasure to meet all of you!

Have a suggestion or something you’d like to see in a future newsletter? Reply to let us know. 🙏

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 & announcements

[Announcement #ABL] Announcing the new Timescale Cloud, and a new vision for the future of database services in the cloud

The cloud is the future - and yet we find that the current landscape of cloud database offerings is lacking. Developers can choose between DBaaS (flexible but a configuration nightmare) and Serverless Data Platforms (easy to use but a black box to users), but they don’t have the option to run a database that is both simple and transparent. In his blog post, our co-founder and CTO Mike Freedman explains how we aim to change that with Timescale Cloud, a modern data platform that combines the ease of use expected from a cloud service with the flexibility and transparency that developers need.

[Product Release #ABL] Support for OpenTelemetry traces in Promscale

Promscale, the observability backend powered by SQL, now includes not only support for Prometheus metrics, but also for OpenTelemetry traces! 🎊 This gives users the ability to query their traces and metrics together and with full SQL. With Promscale, you can query your observability data as you would do with a plain PostgreSQL table, build Grafana dashboards using plain SQL, and integrate it natively with tools like Jaeger or Zipkin.

  • 👉 Read this blog post to learn everything about traces and Open Telemetry. We explain how traces can be a game-changer for your observability practice - and we also show you (through practical examples) how SQL can be incredibly powerful for analyzing your traces 💫.
  • 🐥 See the Twitter thread for the highlights.
  • 📺 Watch the discussion (and live demo) between Ramon Guiu (Timescale VP of Observability) and Ryan Booz (Director of Developer Advocacy) about Promscale and traces!

[Product Release #ABL] New plans for Azure and GCP on Managed Service for TimescaleDB

If you are a user of Managed Service for TimescaleDB in Azure and GCP, now you have 12 more compute and storage options to choose from! Thanks to these intermediate plans, you can now better pick the plan which suits the needs of your workload for maximum cost-efficiency 💰

[Product Release #ABL] Function pipelines: Building functional programming into PostgreSQL using custom operators

Have you ever wished that you could use functional programming in SQL? This is exactly what function pipelines allow you do to 🎉 This new functionality (100% SQL compliant!) allows you to analyze data by composing multiple functions, significantly improving the ergonomics and simplicity of your complex SQL code.

[Product Update #ABL] Grow worry-free w/ storage autoscaling on Timescale Cloud

Do you hate full disks? We sure do – and that’s why we built storage autoscaling, a new Timescale Cloud feature that allows you to scale up from 10 GB to up to 16 TB automatically and without downtime 💯 with user-defined limits to keep costs under control.

[Product Update #ABL] Large storage plans (12, 14, 16 TB) now available in Timescale Cloud

Are you running Timescale Cloud in production? We have good news for you 🔥 Timescale Cloud now includes 12, 14, and 16 TB disk sizes! This means that you can now store and analyze 200+ TB of data on Timescale Cloud (thanks to TimescaleDB’s powerful hybrid compression).

[Community Update] Changes in TimescaleDB Slack

We also wanted to let you know that we made a few additions to our Timescale Community Slack. If you haven’t visited our Community Slack in a while, come say hi! We’re planning on many more community enhancements – stay tuned!

  • 💻 Join the new #show-and-tell channel to share news about your projects, see what other community members are building with TimescaleDB and Promscale.
  • ✨ Join #timescale-live for info on live events, Office Hours, Twitch Streams, and so on.

New technical content, videos & tutorials

[New Benchmark #ABL] What is ClickHouse, how does it compare to PostgreSQL and TimescaleDB, and how does it perform for time-series data?

In Timescale, we like to say that we prefer benchmarking over “benchmarketing”- and we think you’ll agree with us after reading this blogpost. In this 30-minute read, Ryan Booz takes you through a journey into the ClickHouse architecture, describing which aspects of ClickHouse we think are clear strengths 🙏 and which ones could be more problematic - of course, backing up everything with data 📊. These are the results of months of dedicated teamwork… Read the full article to find out our conclusions!

New #remote-friendly events & community

Replay talks from Timescale Community Day

Timescale Community Day 2021 was a blast! We can’t wait to do this again soon. Replay the live stream to learn about all things time-series, TimescaleDB, databases, PostgreSQL, and more. Get expert tips, and much more!

Replay our talks from PromCon NA 2021

Team Timescale had a blast at PromCon and KubeCon North America 2021 (Los Angeles and virtual)!  Replay the talks from Timescale’s Promscale engineers Matvey Arye and Harkishen Singh to get a break down on how to use Promscale and Prom-migrator to aggregate, migrate, manage, and analyze @PrometheusIO metrics (together with more observability data 📈 ).

[Virtual Meetup] Timescale monthly Office Hours (December 7)

If you haven’t joined our monthly sessions yet, now’s your chance! Office Hours are always different - with topics ranging from best ways to integrate with third-party tools to musings on open-source technology - and always chock-full of expert advice, community projects, and fun.

[Virtual Event] All Day DevOps (October 29)

Want to see more of the Promscale magic in action? Replay Vineeth Pothulapati's talk from October 28th to learn how he deploys a full observability suite into his Kubernetes cluster in only a single command and under five minutes!

  • 📺 Sign up to whova.com to watch Vinneth´s talk Deploying a full Kubernetes observability stack in under five minutes.

TimescaleDB tips, reading list & more

[New Blog #ABL] A different and (often) better way to downsample your Prometheus data

Often, users downsample their observability metrics using Prometheus recording rules - but there are cases for which this downsampling method can be sub-optimal. This blog post introduces you to another way to downsample your observability data in Promscale - taking advantage of TimescaleDB continuous aggregates ✨ This will allow you to query and store your observability data with higher efficiency, keeping your data around longer with reduced costs.

[Reading List] PostgreSQL vs Python for data evaluation: what, why, and how

Get a primer on using TimescaleDB and PostgreSQL to perform your data evaluation tasks more efficiently - accomplishing what you were previously doing in Excel, R, or Python but without leaving Postgres. We also include a short (but useful) SQL refresher section in the blog post.


Tweet of the Month

Shoutout to Ivan Murato for sharing his experiences with compression. Thanks for being such an awesome member of the TimescaleDB community! 🙌
  • Visit our docs to read more about compression and how to enable it to save storage and speed up your queries.

Wrapping Up

And, lastly, if you know someone who'd like to join our team – or learn more about life on Team Timescale 🐯 – 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

📆 To see past issues of this newsletter, check out our archives.

This post was written by
7 min read
Newsletter
Contributors

Related posts

TimescaleDB - Timeseries database for PostgreSQL

Explore TimescaleDB

Learn more about how TimescaleDB works, compare versions, and get technical guidance and tutorials.

Go to docs Go to products