🐯 @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.

⚡ TimescaleDB 2.27 is out. The theme: compressed data should do less unnecessary work across the full SQL workload. Reads, writes, mutations. Thread 🧵

At Hannover Messe 2026, Tiger Data co-founder and CTO Mike Freedman sat with @IIoT_World co-founder Lucian Fogoros to break down how @TimescaleDB runs 10x faster than SQL Server, Oracle, or MongoDB at a fraction of the footprint. They also covered the formal partnership with Inductive Automation after seven years of organic Ignition Community adoption, and the launch of TimescaleDB Enterprise for facilities where data cannot leave the building. Full interview on YouTube: youtu.be/p1sUI-qVfU4

Why do Postgres servers fall victim to OOM-killers despite having seemingly sound configurations? At Swiss PGDay on June 25, @TigerDatabase platform engineers @hintbits and Dimitris will share an intensive exploration of the failure path. They'll examine the complexities of Linux overcommit, cgroups, and Postgres memory architecture to understand why the kernel issues a SIGKILL. ⚡ The session will also highlight how eBPF was utilized for troubleshooting and how combining Patroni hooks with Postgres extensions can create a dependable memory ceiling. This deep dive offers a debugging experience that provides profound insights into both Linux and #Postgres operations. Link below.

Postgres is the database that keeps on giving. Latest example: @Azure HorizonDB includes first-class support for pg_textsearch by @TigerDatabase. Love how the Postgres community is coming together to build the last database anyone will ever need. Postgres for Search. Postgres for AI. Postgres for Everything. techcommunity.microsoft.com/…

CERN generates hundreds of gigabytes of time-series data every day from 800 SCADA systems supporting some of the world's most complex physics experiments. Their legacy archiving stack couldn't keep up. By rebuilding on TimescaleDB (Tiger Data), @CERN achieved 95% storage reduction and 40% faster historical analytics, while keeping dashboards responsive across decades of data. Join CERN engineers Rafal Kulaga and Martin Zemko on June 25 at 9 AM ET as they share the architecture, design decisions, and lessons learned from building the NextGen Archiver. Free to attend. Register below. tsdb.co/nk3odc51 #PostgreSQL #TimeSeriesData #IndustrialData #IoT #TimescaleDB

ApexAnalytica renders a year of hourly building telemetry from 38 sites as a single heat map. 6 seconds on vanilla Postgres. Under a second on TimescaleDB hypertables time_bucket MVs. Read how Andrew McKenna built it solo: tsdb.co/lgcewpdo #TimescaleDB #PostgreSQL

Revert all changes to the last savepoint. Let your agents cook, then clean up when they make a mess of everything. 😀

Agents love files. The problem is that files were never designed for agents. No transactions. No isolation. No safe undo. TigerFS turns Postgres into a transactional filesystem. With TigerFS 0.7, released today, we've added arbitrary rollback. Every filesystem operation is recorded in a history log, allowing you to undo changes from a named snapshot, revert a single file or operation, or selectively undo the work of a specific agent. Git is great for collaboration. It's less great as an undo log for AI agents. Don't trust agents to clean up after themselves. Give them an undo button. tigerfs.io

We’re heading to #AWSSummitLA on June 10 - booth 115. Running Postgres on AWS and hitting query slowdowns? Come see how Tiger Data keeps analytics fast on live data without requiring a second database. Book time with the team: tsdb.co/wlety9mo

Every Postgres INSERT is 3 writes in one: heap pages, index pages, and WAL. One 1 KB row produces ~2.5 KB of committed I/O. Here's the anatomy: The WAL double-write is the structural floor. Every byte you insert is written at least twice: once to WAL for crash safety, once to the data file. No tuning removes this. It's why Postgres survives a power cut. Full-page writes compound it after checkpoints. First write to any page triggers a write of the full 8 KB block into WAL. One 1 KB insert touching 6 pages: 48 KB of WAL. That's the spike in your throughput graph right after a checkpoint. The tuning floor: ~2.5x. You cannot go below 2x. Past the floor, it's not a config problem. It's a workload-fit problem. Full breakdown: tsdb.co/amp-tax-x #PostgreSQL

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

Putting a real public app on the internet shouldn't cost $25/month for managed Postgres alone, before you've added compute or even shipped a feature. Today, you can launch a public-facing, sparse-traffic hobby app, backed by Postgres, for roughly the cost of a coffee per month. That's $2/month, folks. @ghostdotbuild gives you the database, @flydotio gives you the compute, and your agent does the rest. dev.to/ghostbuild/ship-an-ap…

Reflecting a bit on all the excitement around the emerging AI factories being built. New chips from companies like @cerebras, alongside major players like Nvidia, are a huge part of the story. But behind them is also a massive buildout of physical infrastructure: buildings, power systems, energy consumption, cooling, water, networking. These systems generate enormous volumes of operational data that need to be monitored in real time, stored historically, and analyzed continuously. We're seeing this firsthand. @TimescaleDB is getting built into the physical and engineering plans of these 21st-century engines. This is the new physical infrastructure powering our digital world. And I'm excited Tiger Data gets to play a small part in powering it.

Today made a video about TigerFS, a great tool by @michaelfreedman that marries the filesystem and the database. "The filesystem is the API (with TigerFS)"

What a quarter. Had ~2x expected revenue growth, our largest net revenue growth month ever in April, and accelerating at scale. The most exciting part is what's driving it: industrial, manufacturing, energy, robotics, and datacenters. AI isn't just changing software. It's driving a re-industrialization wave, and that wave needs modern data infrastructure for machines, sensors, operations, and real-time intelligence. We're seeing it directly in our users. The physical world is coming online, and it runs on data.

Last day at IoT Tech! 🚀 The team is at booth 104 and ready to chat all things databases, time-series, and building faster with modern data infrastructure. Stop by, say hi, and let’s talk data! tsdb.co/3gr6qfe5

Very pleased that @TimescaleDB is financially supporting the continued development of @pgBackRest. To many more years of robust backup/recovery!

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 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-x #PostgreSQL

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. 🎉