Citus 12.1 is out! Now with PG16 Support. Read all about it in Naisila’s 12.1 blog post. 💥
Most of us who work with open source like working with open source. You get to build on what’s already been built, and you get to focus on inventing new solutions to new problems instead of reinventing the wheel on each project. Plus you get to share your work publicly (which can improve the state of the art in the industry) and you get feedback from developers outside your company. Hiring managers give it a +1 too, since sharing your code will sometimes trigger outside interest in what you’re doing and can be a big boon for recruiting. After all “smart people like to hang out with smart people”.
One of the (countless) benefits of working with open source is that it’s so much easier to try things out. Even at four o’clock in the morning, when the rest of the world seems like they’re asleep. We’ve come a long way from the years when the only way to try out new software was to secure an enterprise “try & buy” license: through a salesperson, during business hours, and only after you were done playing an annoying game of phone tag.
Today, when you’re hunting for a new way to solve a problem and you want to try out a new technology, that ability to download open source packages and be up and running in minutes takes a lot of friction out of the process.
And the transparency of the open source culture goes beyond the sharing of source code. Being transparent about both the good and the bad of working with open source can help to promote best practices as well as helps to make things better. Lots of you also share your stories about how you solved a problem, built a thing, or created an order of magnitude efficiency. Whether by conference talk, case study interview, or blog post, we love it when users and customers of the Citus database share their stories about what their challenges were and how they solved their problems.
So we were understandably jazzed when Principal Engineer Min Wei of Microsoft gave a talk at PostgresOpen a few months ago. In Min’s talk, he walked the audience through the architecture of how he uses Citus and Postgres to manage Windows device telemetry to support an executive decision dashboard. Min has built a 700 core Citus database cluster on Microsoft Azure that ingests and deletes 3TB of data per day and handles 500 TB of read IO every day (in fact, every row will get read 10s of times each day.)
We agree with Min when he says that, “Distributed Postgres will be the future for large scale machine learning.”
This year we’ve had the privilege of talking to 12 Citus customers about how they’ve used the Citus database for their multi-tenant SaaS applications and their real-time analytics use cases and their time series workflows. Interviewing these CTOs and Engineering Leaders is one of the most fun parts of my work. And for those of you who are building applications that need the performance of a distributed database that is relational (and that is Postgres, more specifically), it can be useful to hear how another CTO or another data architect has solved their problems. Big thank you to these people (you know who you are), and yet another +1 for the sharing economy.
Talk about burying the lede. This section is the whole reason for this blog post.
Updated 2021: We love it when Citus open source users and customers share stories about how and why they use Citus. Like this Citus story from Algolia on building real time analytics at scale with Citus—or this story from Stackify about calculating percentiles at scale with Postgres, t-digest, and Citus. We also like hearing stories from our own team, including this Software Engineering Daily podcast interview with one of our co-founders titled: "Citus Data: Founding to Acquisition with Umur Cubukcu."
If you use Citus (open source, Citus Enterprise, or our managed service on Azure, we'd love to hear from you. This post is your official invitation to let us know how you're using Citus and what's working (and even what's not.) You can always reach us at @citusdata on Twitter, as well as on our Citus Public slack.