As we head into the new year, we’d like to take a moment to reflect on 2017 and thank everyone who has helped us along the way. So, to our users, developers, community members (especially those of you active in our Slack channel), investors, partners, and all our other cheerleaders: Thank You.
In 2017, PostgreSQL became the fastest growing database in the world, and time-series continued its reign as the fastest growing database category (source: DB-Engines). So it makes sense that 2017 would also be the year that someone launched a time-series database built on top of PostgreSQL: TimescaleDB.
We officially launched TimescaleDB on April 4th, 2017, and were pleasantly surprised by all the positive feedback (special shout out to the PostgreSQL community!). And then, just months after our launch, we found that users were already deploying TimescaleDB successfully into production environments and planning new applications around the database.
Now, nine months later, businesses worldwide already trust TimescaleDB for mission-critical applications from industries as varied as manufacturing, finance, utilities, telecom, mining, ad tech, oil & gas, and the smart home. Applications built on TimescaleDB include complex monitoring systems, industrial machine data analysis, geospatial asset tracking, operational data warehousing, and financial risk management.
Look to the stars
Our growth is reflected in our GitHub stars (a mechanism that allows GitHub users to bookmark open source repositories that interest them):
From 0 to over 3,400 stars in less than a year. Thank you everyone!
As you can see in the graph above, our 2017 was marked by several inflection points:
But that was the past, and now our focus is on 2018. There’s already a lot in the pipeline that we can’t wait to share with you. Stay tuned!
Until then, whether you’ve been steadily following our progress or are just learning of Timescale, be sure to download TimescaleDB and join us in Slack.
How OpenSauced Is Building a Copilot for Git History With pgvector and Timescale
