🐯 @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.

Task 2 of Tiger Hunt: create a hypertable. One line of SQL. Your table gets partitioned by time automatically, so queries stay fast as rows pile up instead of degrading until someone schedules a migration. That's why you do it early. tsdb.co/tiger-hunt-x

Fork production. Test everything. Push verified changes back. That's how Tiger CLI + MCP Server lets you ship database updates safely. No more schema change anxiety. piped.video/4WiAeINv6qM?si=9iG2…

📸 Got yours? Post a pic, tag @TimescaleDB, and use #TigerHunt2026. We'll reshare our favorites. 😉

The first Tiger Hunt boxes are going out. Tee, hat, stickers. Earned, not handed out. Not too late to start. Five hands-on tasks in Tiger Cloud and one of these ships to you. tsdb.co/hunt-unboxing-x #earnyourstripes #jointhetigerhunt #TigerHunt2026

Four out of five Tiger Hunt tasks you can do at 11pm on a Tuesday. Task 5 is a workshop, and those have dates on them. Plan around it. tsdb.co/tiger-workshops-x

25x faster queries. 98% compression. 5-minute database forks. Zero-downtime migration. When Companion.energy hit scaling limits on Azure PostgreSQL, they didn't split their architecture. They switched to Tiger Cloud—unlocking skip-scan and compression features that turned a crisis into a scalable foundation. Not only did they complete the migration in 8 weeks with zero downtime, but they also scaled from 1.7TB → 39GB. Zero rearchitecture needed. Read how: tsdb.co/xtytbye5

We're at IMTS 2026. Booth #236355, Sept 14-19, Chicago. If your shop floor data is outgrowing vanilla Postgres, come find us. tsdb.co/imts26-x-booth

Postgres turns 40 this year. Despite having a name only a parent could love, it's still the database developers know and love most, even in the AI era. We asked five industry experts why. tsdb.co/40yo-db-ai-x @editingwhiz @sogrady @databaseguru @pgillin

Robot training data is scarce and has to be manufactured. Operational data is the opposite: a firehose from every deployed machine. Most stacks keep three copies of it fighting to stay in sync. That's how a failure annotation never reaches the next model. tsdb.co/c3po-x

Industrial historian workloads are changing. More tags. More history. More demanding queries. Meet us at Ignition Community Conference 2026, as we preview an exciting new product announcement. 📍 Sacramento 📅 Sept 22–24 🎤 @michaelfreedman: Building the Modern Historian for Industrial Scale Register for the private preview: tsdb.co/icc26-announce-x

Every historian approach comes with a tradeoff. Embedded historians are simple, but can hit limits as industrial data grows. SQL-based approaches offer flexibility, but often leave teams responsible for database design, tuning, and operations. At ICC 2026, Tiger Data Co-Founder and CTO @michaelfreedman will present: Building the Modern Historian for Industrial Scale See how TimescaleDB is being applied to the next generation of industrial historian workloads, and be there as Tiger Data and Inductive Automation unveil a new approach to the modern historian. Join us for a first look. Tuesday, Sept. 22 | 11:30 AM–12:15 PM tsdb.co/icc26-pre-x

The Tiger Data team is on the ground at IMTS 2026 next week. Find us at booth #236355, Chicago, Sept 14-19. Let’s chat about Postgres built for live analytics on sensor data. tsdb.co/imts26-x-team

We're excited to announce that Tiger Data now connects to Amazon Quick via MCP for energy & utilities customers. Learn more at aws.amazon.com/energy-utilit….

Tomorrow: Join @TigerDatabase 's Erin Mikail and our own Rosendo Pili for a Fireside Chat. Tune in 10:30AM ET: twitch.tv/mlh

🎉 Week 130 — Venture with Grace Week 130 explored AI-native growth, healthcare voice agents, intellectual property, autonomous construction, AI voice infrastructure, and the next generation of enterprise data systems. Week 130 lineup: @georgebonaci, VP at @tryramp: AI-first growth and demand generation in the modern B2B landscape @jain_ankit, CEO at @InfinitusAI: AI voice agents in healthcare and automating complex patient and provider workflows Paul Lee, CEO at Patlytics: AI, patents, and transforming intellectual property strategy with intelligent technology @bsofman, CEO at @BedrockRobotics: Autonomous construction and bringing AI-powered robotics into the physical world @rissa_cao, CEO at @FishAudio: AI voice infrastructure and building expressive, scalable voice technology @bryantchou, CEO at @ployai: AI agents, marketing automation, and the future of web growth @acoustik, CEO at @TigerDatabase: Postgres, AI agents, and the data infrastructure powering intelligent applications Another packed stretch of conversations — with a clear takeaway: AI is moving deeper into real-world workflows, from healthcare and construction to marketing, voice, IP, and the data infrastructure underneath it all. More coming next week. See you live 👋 #VentureWithGrace #AI #startups #founders #vc #AIAgents #AIInfrastructure #Robotics #EnterpriseAI

Listen to my conversation with @acoustik of @TigerDatabase on Spotify: bit.ly/3v1R0Tu Apple: bit.ly/4bTCwpD Youtube: bit.ly/3uXthnv LinkedIn: bit.ly/3Xs8GQP Website: svppro.com ~~~~~~~~~~~~~ This episode is brought to you by Nebius — the ultimate cloud for AI innovators. Nebius provides AI infrastructure you can count on, combining reliability and speed with flexibility and engineering support unmatched by hyperscalers. AI leaders like Meta, Shopify, and Higgsfield already partner with Nebius to run their AI workloads. Plus, venture-backed startups can save up to $150,000 on compute costs when they apply for access. Visit nebius.com or nebius.com/startups to learn more ~~~~~~~~~~~~~ #ArtificialIntelligence #PostgreSQL #AIInfrastructure #Database #AIEngineering

Doug Pagnutti from Tiger Data built a SCADA system at a manufacturing plant. It worked great for about 18 months. Then the database filled up, dashboards slowed to a crawl, and he ended up shelving hard drives full of production data nobody could access. TimescaleDB on PostgreSQL handles both relational and time-series data with 90% compression, so the database keeps up. Partner content with @TigerDatabase. Visit Tiger Data at #IMTS this week. #tigerdata_ai #IMTS2026

Doug Pagnutti from Tiger Data on a use case he wouldn't have expected a couple of years ago: energy management. Manufacturers are slowing down energy-intensive processes when electricity prices spike and adjusting production around the grid. With power getting more complicated, real-time data for those decisions saves real money. Partner content with @TigerDatabase. Live from IMTS, Sept 14-19 in Chicago. #tigerdata_ai #IMTS2026

Doug Pagnutti from Tiger Data: machine learning found humidity was driving the tuning on a powder dosing system, something the team never suspected. On the troubleshooting side, AI helps engineers reach root causes faster instead of applying band-aids. Partner content with @TigerDatabase. Tiger Data at IMTS, Sept 14-19. #tigerdata_ai #IMTS2026

Doug Pagnutti from Tiger Data lived the classic factory data problem firsthand: buying bigger servers that didn't help, dropping tags to make room, disconnecting hard drives full of production data. 10 years later, GenAI finally makes that data valuable, but most plants already deleted the high-resolution records those models need. TimescaleDB solves that at the architecture level. Partner content with @TigerDatabase. Find out more from Tiger Data at #IMTS2026. #tigerdata_ai