Scaling Time-Series Workloads on Postgres

Many real world processes produce data as a continuous stream rather than as isolated records. Sensor readings, financial markets, and application telemetry all generate data this way. This kind of time series data has a distinctive shape. It's written far more often than it is updated, it accumulates continuously, and it is usually queried across ranges of time. Time series databases are built specifically for this kind of workload. TimescaleDB is an open source database from Tiger Data that adds time series capabilities to PostgresQL. It's implemented as a Postgres extension, so it introduces new functionality while preserving standard Postgres behavior and SQL. This lets a single Postgres based system handle both transactional and analytical workloads without splitting data across multiple tools. Brandon Pursell is the director of product management at Tiger Data. In this episode, Brandon joins Kevin Ball to discuss why time series data breaks conventional databases, how HyperTables and HyperCore scale Postgres, zero copy database forking for agent based workflows, and much more. Kevin Ball, or Kate Ball, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co founded and served as CTO for two companies, founded the San Diego JavaScript Meetup, and organizes the AI in Action discussion group through Latent Space. Check out the show notes to follow k ball on Twitter or LinkedIn or visit his website, kball.llc. Brandon, welcome to the show. Yeah. Thanks for having me, Kevin. Yeah. I'm excited to learn a little bit more about what you're up to. So let's start with you. Can you give us a quick overview of your background and then how you ended up at Tiger and what you're doing there? Yeah. No. Absolutely. I've been working in the tech industry for a very long time. Spent my early years in the military, even writing code, and then started working at Adobe soon after that, working in a number of different roles there. And met a couple of guys when we built a startup. Startup was called SpatialKey. So the background in my area and experience in Postgres goes back almost twenty years. And we built a geospatial analytics platform that was built on top of Postgres, primarily initially focusing across a broad range horizontal, but then switching that into insurance and everything from underwriting to event response and portfolio management type use cases. And probably after about thirteen years, we sold the company. And I spent some time, took some time off afterwards, and decided to come back and actually take a very different role. I was doing mostly leadership. I was the CTO of the company and really wanted to get back into the tech side of it and product. And I love Postgres, and so ended up coming over to Tiger Data because I believe they have a great product and it really takes Postgres to the next level. That's a good intro. So can you tell us a little bit about …