Timescale Newsletter Roundup: February 2021 Edition
In this edition, we’re sharing two new open-source tools from the Promscale team, announcing that TimescaleDB 2.0 is officially generally available, shining a light on community members’ work, and giving you an assortment of our favorite tools, tips, and advice for doing more with your time-series data.
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
[Product Announcement #1]: TimescaleDB 2.0 is generally available & production-ready >>
We’re excited to share that TimescaleDB 2.0 is officially Generally Available for self-managed, Timescale Cloud, and Timescale Forge users! This milestone release includes new features and capabilities - including multi-node for ultimate scale, substantial enhancements to continuous aggregates, advanced customization options, and more.
- 🔎 Read our blog to learn what’s new and how to get started, complete with example queries, why we’ve evolved TimescaleDB over time, and what’s coming next.
- 🐥 See our Twitter thread for the highlights & join in on the conversation.
- 🎬 Watch All Things TimescaleDB 2.0 playlist for feature-specific demos and best practices.
- 📥 Subscribe to our Release Notes to get all product updates straight to your inbox.
[Product Announcement #2]: Introducing Tobs: Deploy a full observability suite for Kubernetes in two minutes >>
Get an in-depth look at Tobs, our new open-source tool that deploys a full observability suite for Kubernetes, in minutes. Our goal: make observability more accessible to more developers, removing the need to compromise on flexibility, ease of use, or cost.
- ✨ Find Tobs on GitHub - issues and pull requests welcome!
- 🐥 See @cevianNY’s Twitter thread to learn more (including why we think open-source is the future of observability).
[Product Announcement #3]: Introducing Prom-migrator: A universal, open-source Prometheus data migration tool >>
We recently released Prom-migrator - an open-source tool that makes it easy to migrate your Prometheus data to and from popular remote-storage systems. Learn how and why we built it - including the problems it solves - and see how to get started with two sample scenarios.
- 🎥 Watch our demo to get up and running in <10 minutes.
- ✨ Find Prom-migrator on GitHub to get started right away.
- 🐥 See our Twitter thread for the highlights & join in on the conversation.
New technical content, videos & tutorials
[Time Series Benchmark Suite]: Benchmarking 200+ billion metrics with TimescaleDB compression & user-defined actions >>
Follow along as @ryanbooz uses the Time Series Benchmarking Suite to put Timescale Forge through its paces and solves a seemingly impossible task: ingesting 200B+ metrics (10+ TB of data) into a database with only 1TB of storage. Compression and user-defined actions to the rescue. ✨
- 📏 Learn how to use user-defined actions (new in TimescaleDB 2.0).
- 🔎 Read how TimescaleDB compression works.
[Grafana Watchlist]: Guide to Grafana 101 >>
In a series of 4 demo-filled technical sessions, our resident Grafana pro @avthars takes you from zero to dashboarding hero. You'll cover everything from building awesome, interactive visualizations to setting up custom alerts, sharing dashboards with teammates, and solving common issues. (Plus tips and resources to apply concepts to your projects. 🔥)
New #remote-friendly events & community
[Office Hours]: Join us for our monthly community Q&A and time-series watercooler >>
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.
- 🗓 RSVP for an upcoming session.
- 💬 If you can’t join, but have a question, reach out to our engineering team on Slack.
Learn how our friends @TeamConserv use time-series data to help collections care professionals around the world protect historical artifacts, get their advice for aspiring developers, and more.
TimescaleDB tips, reading list & more
[TimescaleDB 2.0 Tip #1]: How to work with real-time aggregates in TimescaleDB 2.0 >>
Developer Advocate @ryanbooz examines how real-time aggregates work in TimescaleDB 2.0, clears up common misconceptions, and breaks down how the query planner works, specifically when data hasn’t been materialized. Result: you avoid inefficient query plans and get all of the right pieces in place.
- 🔧 Check out what’s new in TimescaleDB 2.0.
- 🔎 Read our engineering blog post for details about our journey to TimescaleDB 2.0, sample queries, and what’s coming next.
[TimescaleDB 2.0 Tip #2]: What data is actually stored in continuous aggregates? >>
Developer Advocate @ryanbooz examines how continuous aggregates work in TimescaleDB 2.0, clears up common misconceptions, and walks through a few examples to help you set up continuous aggregates to return the data you want.
- 🔎 Check out our continuous aggregates docs for more guidance, sample queries, and advanced scenarios.
- ✨ As a reminder, TimescaleDB is officially Generally Available (read our engineering blog post for details) 🥳.
[TimescaleDB 2.0 Tip #3]: Use continuous aggregates to speed up your time-series queries >>
TimescaleDB 2.0 includes significant improvements to continuous aggregates, but what are they and how can they help you? This step-by-step guide shows you how to use continuous aggregates to speed up the queries you run frequently, automatically refreshing and loading results at custom intervals.
- 💻 See our overview for more about how continuous aggregates work.
[Reading List]: How to manage long-term data storage with downsampling >>
Learn how downsampling, data retention policies, and continuous aggregates allow you to perform historical analysis on your data, without sacrificing performance or incurring massive costs. We use a DevOps scenario to demonstrate what downsampling is, how it works, why it’s so powerful, and how to get up and running in 3 steps.
- 🍿 Prefer video tutorials? Watch our 10-minute demo.
[Community Watchlist #1]: Install TimescaleDB 2.0 (multi-node) on Kubernetes using Helm >>
@PraveenPerera takes you from zero to running multi-node TimescaleDB on Kubernetes in <7 minutes. Follow along as he reviews prerequisites, uses Helm to install TimescaleDB 2.0, accesses the database locally, and beyond.
- ✨ See accompanying text-based tutorial.
- 🔧 See TimescaleDB Kubernetes repo to recreate Praveen’s walkthrough + deploy on your clusters.
[Community Watchlist #2]: TimescaleDB for Finance: Python, Docker, Alpaca & more >>
@PartTimeLarry’s 6-episode series takes you from “what is time-series?” to building an ETF database, designing your schema, analyzing ARK buy/sell trends, Reddit and Twitter mentions, and more - complete with 💯 commentary and detailed explanations.
- 🛠 Check out Larry's ARK Funds Tracker project (GitHub).
- 👟 Explore our Python & TimescaleDB quickstart for installation tips and sample queries.
[Team Timescale]: Join Timescale heroes program >>
If you love time-series data, TimescaleDB, and helping community members learn how to do more with their data, Timescale Heroes is for you! We equip you with demos and resources to make your projects and presentations shine, partner with you on content, and make sure you have the latest swag.
[Community Reading List]: The shifting market for PostgreSQL >>
👏 to our friend @mjasay for breaking down why PostgreSQL is more popular than ever.
"PostgreSQL has been around in some form since 1986, yet somehow keeps getting younger and hipper with each year. Startups like Timescale have found old-school PostgreSQL to be key to building their new-school database products, joining companies like EDB in deepening PostgreSQL’s popularity." - Matt Asay
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).