Timescale Newsletter Roundup: August Edition

3 exciting product releases (including big news for Timescale Cloud), 2 amazing community member shoutouts, 1 "Postgres Pro Tips" technical series, and oh so many tutorials, events, and how-tos to help you continue your journey to data mastery 🎉.

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).

New technical content, videos & tutorials

[Session Replay]: Postgres Pro Tips Part I: 5 Ways to Improve Your PostgreSQL INSERT Performance >>

Our resident webinar pro @avthars breaks down factors that impact PostgreSQL ingest rate and 5 immediately actionable ways to improve your database speed. You’ll learn why ingest rate is so critical to time-series data and get step-by-step demos, tips, and resources to apply each optimization to your apps.

👉 Get 13 tips in this blog post from Timescale CTO Mike Freedman.
🔨 Explore the Time-Series Benchmarking Suite to replicate Avthar’s demo (or benchmark the performance of any time-series database).

[Postgres Pro Tips Part II]: 5 Powerful PostgreSQL Functions for Monitoring & Analytics >>

PostgreSQL is ideal for real-time monitoring and historical analysis, but writing efficient queries can be tricky. Join @avthars to learn how to build essential PostgreSQL functions for common real-time scenarios, plus TimescaleDB-specific functions to simplify time-series historical analysis.

🗓 RSVP for Wed., Sept 16th
We send the recording + resources to all registrants within 48 hours, so sign up even if you can't attend live.

[NEW How-to]: Using PostgreSQL to speed up Grafana: auto-switching between different aggregations >>

Learn how to use UNION ALL to build graphs that allow you to “auto-switch” aggregated views of your data (e.g., daily, hourly, weekly) in the same Grafana visualization. The result: faster dashboards that allow you to drill into your metrics as quickly as possible and save time and CPU resources.

[NEW How-to]: How to visualize timeshifts in Grafana using PostgreSQL>>

Combine PostgreSQL and Grafana to easily compare your metrics across time periods in one graph. We break down what timeshifting is & how it works, plus step-by-step instructions and sample queries that you can modify for your own projects.

Grafana screenshot showing two dfferent trend lines, one plotting "this week" data and one plotting "-7 days" data — Grafana visualization showing current and last week's data (aka "timeshifted), making it easier to visually distinguish between periods >> compare data and spot trends across time intervals

New #remote-friendly events & community

[Community Q & A]: Join us for Office Hours on Tues, Oct 6th >>

If you have questions about TimescaleDB, from schema design best practices to upcoming releases, or want to learn more about general distributed computing and networking topics, Office Hours - hosted by Timescale technical experts - is for you.

👉 Reserve your spot on Tues, Oct 6th (space is limited)
💬 If you can’t join, but have a question, reach out to our engineering team on Slack.

[Community Spotlight #1] How I power a (successful) cryptobot with TimescaleDB >>

Our friend Felipe Queis shares how he combines ML, TimescaleDB, and Node.js to power a crypto trading bot that’s netted several successful trades (+487%!). He details how his bot works, why he selected TimescaleDB, sample queries, favorite resources, and beyond.

💰 See Felipe’s Reddit AMA for even more tips and technical details.
📈 Read his Hacker Noon post to see how his results have only continued to improve.

[Community Spotlight #2] How FlightAware Monitors its Systems with Prometheus, Grafana, and TimescaleDB >>

Three cheers to @flightaware for their amazing breakdown of how they’ve architected their monitoring stack (and for their work to keep travelers informed, safed, and on-time). You’ll learn why they selected each component and the role it plays in fueling their real-time monitoring, ETA predictions, historical analysis, and more.

📊 Inspired by FlightAware’s Grafana dashboards? Explore 5+ tutorials to build awesome Grafana visualizations with your data.
📣 Have a story to share? Reach out on Slack or @TimescaleDB and we’ll make it happen

Product Updates, Reading List & Etc.

[Product Update #1]: Timescale Cloud gets even better, now available in 75+ regions & 2K configurations >>

We launched Timescale Cloud to allow developers to get the power of TimescaleDB, with worry-free operations and the ability to grow, shrink, and migrate workloads with ease. We’re excited to now offer Timescale Cloud in 75+ regions across AWS, GCP, and Azure and with fine-grained CPU/storage config options - giving you ultimate flexibility and control.

📰 See Hacker News discussion (60+ comments!)
🗞 Check out what Timescale CEO says about the news and what it means for developers.
🙌 Blue Sky Analytics, Everactive & When I Work for sharing your experiences for this post.
🙏 Thank you to all of our Cloud customers & community members.

World map using different colored dots to plot Timescale, Influx, and AWS Timestream cloud regions

[Product Update #2] Timescale Forge now includes CPU, memory & storage metrics reporting >>

Timescale Forge - our second fully managed database for time-series product, currently in public preview - now includes a comprehensive metrics dashboard! Easily analyze spikes in usage, zoom in for more granular understanding, observe correlations between metrics, and identify issues on-the-fly.

🔥 Explore Timescale Forge (100% free for 30 days).
☁️ Learn more and choose the best cloud option for you.

GIF showing Timescale Forge UI metrics dashboard (sections for CPU, Memory, and Storage utilization) — Create your Timescale Forge account to see the new dashboard in action

[Product Update #3]: Timescale Prometheus Adapter now in beta >>

We just shipped our first Prometheus Adapter beta candidate, which signifies we believe our API is now feature complete (although not yet recommended for production workloads)! This release includes tons of updates to improve performance and usability, including support for querying PromQL directly from the connector.

⭐ Get the source code & release notes (GitHub).
✅ We’re also proud to share that our PromQL support passes 100% compatibility tests.
Subscribe to Prometheus Product Updates to get new releases and announcements straight to your inbox.

[TimescaleDB Tip #1]: Build time-series forecasting models with R, Apache MADlib & Python >>

Follow this detailed tutorial to learn how to use TimescaleDB to analyze your data and make predictions. We’ve included guidance for not one, but two approaches: ARIMA and Holt-Winters.

[TimescaleDB Tip #2]: How to install psql on Mac, Ubuntu, Debian, Windows>>

Use this guide to get up and running with #psql on your platform of choice, see common commands at-a-glance, get tips for saving query results, and more.

[TimescaleDB Tip #3]: Explore the price of Bitcoin and Ethereum over time >>

Get step-by-step instructions for connecting to TimescaleDB, designing your schema, and creating your dataset (plus sample queries to kick off your analysis.

[ICYMI]: TimescaleDB vs. InfluxDB: Purpose built differently for time-series data >>

We just refreshed our TimescaleDB v. InfluxDB benchmarks to see how the latest versions stack up across 5+ areas critical to time-series data workloads.

⏰ Check out @avthars Twitter thread to see key points, in 240 characters or less.

[Reading List]: What is high cardinality, and how do time-series databases like InfluxDB and TimescaleDB compare? >>

Get a look into what causes high-cardinality, why it's so common in time series scenarios, and how TimescaleDB solves for it. This old (but good!) post breaks down the basics & details how different databases approach the issue.

⚖ Want more info about how TimescaleDB & InfluxDB compare? Check out our 2020 Benchmark Report.

[Reading List]: Why SQL is beating NoSQL, and what this means for the future of data >>

Check out this Star Wars-infused history of databases, from a New Hope to NoSQL Strikes Back and Return of the SQL. We published this awhile ago, but it’s even more true now (NoSQL < SQL).

[Watchlist]: Lessons learned optimizing relational schema for Prometheus data >>

Catch Timescale Engineer Mat’s PromCon 2020 lightning talk to learn how the team’s building a long-term data store for Prometheus metrics, what they’ve learned along the way, and what’s next.

[Timescale Team Fun]: Last, but certainly not least, we continue to find little ways to stay connected with things like movie-themed Slack challenges and quirky "tell us about you" prompts. Asynchronous communication and team bonding at its finest.

Check out the below for a few examples, which you're welcome (and encouraged!) to reuse to inspire your own remote team activities 💭.

Screenshot of Slack message asking "What was the hottest toy on the market when you were 10 years old?" — Original Nintendo, Power Rangers, and Tamagotchi were clear winners for Team Timescale

Screenshot of Slack message asking "what movie was #1 at the box office the year you were born?"

Screenshot of Slack message "Movie Emoji challenge" with 2 men, a black circle, and alien emoji — Check out this Medium post for more "Emoji Movie challenge" ideas

Wrapping Up

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).