Tiger Data - Creators of TimescaleDB

🐯 @TimescaleDB is now TigerData! 🚀 When we launched Timescale, the top Hacker News comment said it was “a bad idea.” PostgreSQL wasn’t supposed to be fast. Or scalable. Or useful for time-series. 8 years later: -2,000 customers -8-digit ARR -Most workloads aren’t even time-series anymore We’ve changed our name to reflect that evolution: Timescale is now TigerData. Same code. Same team. Still PostgreSQL. Just a lot faster.

Congrats to the Cerebras team on today’s IPO. We're proud to count Cerebras as a Tiger Data customer, and honored to have supported them over the years as they build foundational AI infrastructure. 🎉

I'm attending #AWSSummit in Hamburg next week. Ping me if you'll be there. I would love to chat about Postgres, real-time analytics and time-series.

Big congratulations to the @cerebras team on hitting IPO! 🚀 Incredible to see a customer building at such an impressive scale and continuing to hit major milestones. Excited to be part of the journey!🥳

TimescaleDB will be at #AWSSummit Hamburg. Let’s talk PostgreSQL, real-time analytics, time-series workloads on AWS, and AI applications built on operational data. Book a meeting with our team at the event! tsdb.co/i4nemls3

These results surprised me as well 😅 "Why TimescaleDB Won 96% of Tests"

Postgres internals: your reads are writing to disk. When Postgres reads a new row, it sets a hint bit in the tuple header. That write dirties the page. I/O from reads on "immutable" data. New post: tsdb.co/autovacuum-tax… #PostgreSQL

Teams call it a database migration. That's the wrong mental model. TimescaleDB is a Postgres extension. Same SQL. Same drivers. Same wire protocol. You're not leaving Postgres. You're giving it better tools. tsdb.co/postgres-migra…

Meet the TimescaleDB team at #IoTTechExpo, May 18–19 at Booth #104. We’ll be talking real-time analytics, IoT infrastructure, PostgreSQL, and AI-powered applications built on operational data. Book a meeting with our team at the event. tsdb.co/3gr6qfe5

Postgres write amplification has a floor you cannot tune below. WAL writes every byte twice (log, then data file). Structural 2x. Aggressive tuning gets you to ~2.5x. Anyone quoting less is measuring something else. tsdb.co/amp-tax-x

👥 Live at @SensorsConverge today. Sensor data outgrows your database. The usual fix is a second system, with all the pipelines that brings. Skip the split. Tiger Data extends Postgres. Booth 1342 until 5:30. tsdb.co/sensors-2026-x #SensorsConverge

50 parallel queries. 1M log records. TimescaleDB: 6.2miliseconds vs ClickHouse: 6,307miliseconds A dev built a full observability benchmark (logs, spans, metrics) across 54 tests. TimescaleDB won 96%. Full results: builder.aws.com/content/3Aoryr…

We will be at #OTC2026 in Houston, booth #3810. If your team runs on high-frequency sensor or SCADA data, come find us. Book a meeting: ow.ly/xrsU50YRYCH #OilAndGas #PostgreSQL

We'll be at @SensorsConverge, May 5-7. Booth 1342, Santa Clara. If you're building IoT systems and hitting performance walls as sensor data scales, come talk to us. Book a time: tsdb.co/sensors-2026-x

@flightaware: 6.4s to 30ms. No ClickHouse. No pipeline. Still on Postgres. Before you build a pipeline to feed a second database, worth asking if the problem is the database or the primitives. tsdb.co/jqva64wh

@iqtoolkit Welcome to the jungle! 🐯

Today marks day one of an exciting new chapter! 🚀 I’m thrilled to announce I’m joining @TigerDatabase (formerly Timescale) as a Database Support Engineer. I'll be taking my passion for #PostgreSQL helping teams architect high-performance, AI-ready data systems. Time to build!

Big news: we’re partnering with @InductiveAuto. A modern, SQL-native foundation for industrial data - built for scale, speed, and real-time insight. Read more: inductiveautomation.com/news/inductive…