James Weitzman (@james_weitzman) 's Twitter Profile
James Weitzman

@james_weitzman

GTM leadership @timescaledb, @uofmaryland alum

ID: 423190895

linkhttp://timescale.com calendar_today28-11-2011 06:00:06

199 Tweet

1,1K Followers

988 Following

Timescale (@timescaledb) 's Twitter Profile Photo

Most AI chatbot demos don’t survive production. They skip auth, duplicate data across Postgres + vector DBs, and rely on fragile sync pipelines. We built something simpler—and more secure. 🔒 In our new webinar, Oso and Timescale (now TigerData) show how to build an authorized AI

Timescale (@timescaledb) 's Twitter Profile Photo

June Launch Day 1: Speed without Sacrifice TimescaleDB 2.20 just dropped with performance numbers that will make you rethink what's possible with PostgreSQL. The headline numbers: - 2500x faster DISTINCT queries with SkipScan optimization - 10x faster upserts and backfills on

June Launch Day 1: Speed without Sacrifice

TimescaleDB 2.20 just dropped with performance numbers that will make you rethink what's possible with PostgreSQL.

The headline numbers:
- 2500x faster DISTINCT queries with SkipScan optimization
- 10x faster upserts and backfills on
Timescale (@timescaledb) 's Twitter Profile Photo

🚀 Skip the ETL headaches. Go straight from S3 to PostgreSQL. Traditional ETL pipelines are notorious for creating bottlenecks—data staleness, complex batch processing, and constant maintenance overhead. What if you could eliminate all of that? AWS Solutions Architects Mrinali

🚀 Skip the ETL headaches. Go straight from S3 to PostgreSQL.

Traditional ETL pipelines are notorious for creating bottlenecks—data staleness, complex batch processing, and constant maintenance overhead. What if you could eliminate all of that?

AWS Solutions Architects Mrinali
Mike Freedman (@michaelfreedman) 's Twitter Profile Photo

The OLTP vs. OLAP split made sense when applications and analytics were separate stacks. But today, the real divide is operational vs. non-operational data: data needed to serve the app vs. data optimized for training, analysis, or governance. That’s Postgres + the lakehouse.

Timescale (@timescaledb) 's Twitter Profile Photo

🐯 Timescale is now TigerData! 🚀 Eight years ago, we started as a PostgreSQL-based time-series database. But innovation never stands still—and neither have we. Today, we proudly unveil TigerData - Creators of TimescaleDB, marking our evolution into the fastest and most powerful PostgreSQL

TigerData - Creators of TimescaleDB (@tigerdatabase) 's Twitter Profile Photo

From the creators of TimescaleDB — the fastest Postgres — join us for a two-hour live session built for developers in New York! 👀 See how top teams build real-time apps and AI agents — July 15th 💬 Get answers at the Query Clinic — 1:1 help from TigerData engineers 🔍 Hear

From the creators of TimescaleDB — the fastest Postgres — join us for a two-hour live session built for developers in New York!

👀 See how top teams build real-time apps and AI agents — July 15th
💬 Get answers at the Query Clinic — 1:1 help from TigerData engineers
🔍 Hear
adam bain (@adambain) 's Twitter Profile Photo

These are all amazing initial stats for Baseten on the AI scoreboard — including being the most cost-effective input and output. But the low latency & high throughput story here is really compelling and shows why Baseten is the best place to develop on.