The Data Layer for the AI Data Center
A TimescaleDB technical reference architecture for operational time-series data across AI data centers, from control layer to enterprise rollup.
By Hien Phan
July 8th, 2026
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Lead product marketing at Tiger Data. Previously led product marketing teams at Pinecone, Amplitude, and Mode.
A TimescaleDB technical reference architecture for operational time-series data across AI data centers, from control layer to enterprise rollup.
By Hien Phan
July 8th, 2026
Why AI capacity stopped behaving like elastic compute and started depending on physical infrastructure, power, and place.
By Hien Phan
July 2nd, 2026
Why operating TimescaleDB for mission-critical applications becomes a sustained platform engineering investment. Written by the team that builds TimescaleDB and operates Tiger Cloud across thousands of production deployments.
By Matty Stratton
June 25th, 2026
A practical framework for choosing between self-hosted TimescaleDB and Tiger Cloud: what each path requires, who owns what, and four questions to decide.
By Matty Stratton
June 25th, 2026
Great models aren't enough for Physical AI. Real deployments are gated by regulation, safety, operations, and the data your machines produce.
By Hien Phan
June 18th, 2026
Vector search becomes an index design problem as your data grows. Here's how to make the right call without leaving Postgres.
By Hien Phan
May 26th, 2026
Experiment with AI on Postgres. The Tiger Free Plan offers database forks, vector search, and real-time analytics. No credit card required. Built for developers and agents: Agentic Postgres.
By Hien Phan
October 21st, 2025
Not all analytics are equal—neither are benchmarks. Meet RTABench and compare different databases—from PostgreSQL to ClickHouse—using real-world query patterns.
By Ramon Guiu
March 26th, 2025
Read how we’re scaling Postgres for real-time analytics. No bottlenecks, no specialized infrastructure, all the performance you need.
By Hien Phan
March 17th, 2025
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