Why Influx Rebuilt Its Database for the IoT and Robotics Explosion
Episode description
InfluxDB just dropped its biggest update ever — InfluxDB 3.0 — and in this episode, we go deep with the team behind the world’s most popular open-source time series database.
You’ll hear the inside story of how InfluxDB grew from 3,000 users in 2015 to over 1.3 million today, and why the company decided to rewrite its entire architecture from scratch in Rust, ditching Go and moving to object storage on S3.
We break down the real technical challenges that forced this radical shift: the “cardinality problem” that choked performance, the pain of linking compute and storage, and why their custom query language (Flux) failed to catch on, leading to a humbling embrace of SQL as the industry standard. You’ll learn how InfluxDB is positioning itself in a world dominated by Databricks and Snowflake, and the hard lessons learned about monetization when 1.3 million users only yield 2,600 paying customers.
InfluxData
Website - https://www.influxdata.com
X/Twitter - https://twitter.com/InfluxDB
Evan Kaplan
LinkedIn - https://www.linkedin.com/in/kaplanevan
X/Twitter - https://x.com/evankaplan
FIRSTMARK
Website - https://firstmark.com
X/Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
X/Twitter - https://twitter.com/mattturck
Foursquare:
Website - https://foursquare.com
X/Twitter - https://x.com/Foursquare
(00:00) Intro
(02:22) The InfluxDB origin story and why time series matters
(06:59) The cardinality crisis and why Influx rebuilt in Rust
(09:26) Why SQL won (and Flux lost)
(16:34) Why UnfluxData bets on FDAP
(22:51) IoT, Tesla Powerwalls, and real-time control systems
(27:54) Competing with Databricks, Snowflake, and the “lakehouse” world
(31:50) Open Source lessons, monetization, & what’s next