Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Introducing the latest in Postgres for agentic workloads. Agents can now branch or wake your Postgres database instantly.

xata's profile picture

Xata 🦋

4,098 subscribers

355,417 görüntüleme • 2 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Introducing Database Traffic Control: a Postgres traffic management system built into PlanetScale. Enforce flexible budgets on your database traffic to protect against unexpected and dangerous workloads.
3:30

Introducing Database Traffic Control: a Postgres traffic management system built into PlanetScale. Enforce flexible budgets on your database traffic to protect against unexpected and dangerous workloads.

PlanetScale

161,596 görüntüleme • 5 ay önce

Big moment for Postgres! AI agents broke the idea of what a database is supposed to do. Traditional databases were built for humans, and Agents broke that model. - They branch endlessly. - They run ten experiments at once. - They need isolation, context, memory, structured reasoning, and safe sandboxes. Letting agents touch production systems is terrifying because the old model of Postgres was never built for this kind of behavior. Agentic Postgres is an agent-ready version of Postgres by TimescaleDB (by Tiger Data) that solves this. I think it is one of the biggest upgrades to the Agent stack this year and Tiger Data is working with me on this post to share what they did. Some key features: > It instantly creates branches of an entire database, which is perfect for parallel agent evals, safe experiments, migrations, or isolated testing. Forks take seconds and cost almost nothing. > It comes with a built-in MCP server, which agents can use to get schema guidance, best practices, and safe, structured access to Postgres. This is also helpful to run migrations with a real understanding. > It comes with actual hybrid search (vector search and BM25), so Agents can retrieve data directly inside the database. > The database is Memory native. This gives a persistent context for Agents to evolve. This is one of the first times I have seen Postgres feel ready for the AI native era.
0:26

Big moment for Postgres! AI agents broke the idea of what a database is supposed to do. Traditional databases were built for humans, and Agents broke that model. - They branch endlessly. - They run ten experiments at once. - They need isolation, context, memory, structured reasoning, and safe sandboxes. Letting agents touch production systems is terrifying because the old model of Postgres was never built for this kind of behavior. Agentic Postgres is an agent-ready version of Postgres by TimescaleDB (by Tiger Data) that solves this. I think it is one of the biggest upgrades to the Agent stack this year and Tiger Data is working with me on this post to share what they did. Some key features: > It instantly creates branches of an entire database, which is perfect for parallel agent evals, safe experiments, migrations, or isolated testing. Forks take seconds and cost almost nothing. > It comes with a built-in MCP server, which agents can use to get schema guidance, best practices, and safe, structured access to Postgres. This is also helpful to run migrations with a real understanding. > It comes with actual hybrid search (vector search and BM25), so Agents can retrieve data directly inside the database. > The database is Memory native. This gives a persistent context for Agents to evolve. This is one of the first times I have seen Postgres feel ready for the AI native era.

Avi Chawla

94,290 görüntüleme • 9 ay önce

Your Launchpad for Postgres: Get a Postgres connection URL in seconds, use your DB, claim it later. Perfect for building products like Netlify DB, OSS projects, and agents.
2:31

Your Launchpad for Postgres: Get a Postgres connection URL in seconds, use your DB, claim it later. Perfect for building products like Netlify DB, OSS projects, and agents.

Neon Postgres

21,035 görüntüleme • 1 yıl önce

Introducing dba: The Autonomous AI Agent for Postgres
1:00

Introducing dba: The Autonomous AI Agent for Postgres

Tembo

26,596 görüntüleme • 1 yıl önce

We built a no-signup Postgres tool 📸 - Get a Postgres URL in a second, from your browser or terminal - If you want to keep your database, transfer it to your Neon account It uses Cloudflare, React Router, and Drizzle ORM under the hood
0:27

We built a no-signup Postgres tool 📸 - Get a Postgres URL in a second, from your browser or terminal - If you want to keep your database, transfer it to your Neon account It uses Cloudflare, React Router, and Drizzle ORM under the hood

Neon Postgres

26,526 görüntüleme • 1 yıl önce

🚨 Tiger Data - Creators of TimescaleDB (Yes! the team behind TimescaleDB) is quietly revolutionizing how we build agents. The Old Way: Glueing together Postgres + Vector DBs + Search tools = complexity. The New Way: Tiger Data’s Agentic Postgres handles it all natively 🔥 What’s now possible 🧵 ↓ ✦ Hybrid retrieval → combine keyword filtering and vector similarity in a single query ✦ Forkable databases → retrieval and safe experimentation without external systems ✦ Native Postgres semantics → everything stays queryable, inspectable, and debuggable in SQL Why this matters: → Fewer moving parts in RAG pipelines → No extra infrastructure to stitch together → Agents can iterate and learn safely → Production data stays isolated and protected This is an awesome shift! Stop bolting workflows onto your database. Let your database be the workflow 🔥
0:38

🚨 Tiger Data - Creators of TimescaleDB (Yes! the team behind TimescaleDB) is quietly revolutionizing how we build agents. The Old Way: Glueing together Postgres + Vector DBs + Search tools = complexity. The New Way: Tiger Data’s Agentic Postgres handles it all natively 🔥 What’s now possible 🧵 ↓ ✦ Hybrid retrieval → combine keyword filtering and vector similarity in a single query ✦ Forkable databases → retrieval and safe experimentation without external systems ✦ Native Postgres semantics → everything stays queryable, inspectable, and debuggable in SQL Why this matters: → Fewer moving parts in RAG pipelines → No extra infrastructure to stitch together → Agents can iterate and learn safely → Production data stays isolated and protected This is an awesome shift! Stop bolting workflows onto your database. Let your database be the workflow 🔥

Chaz Wargnier ♨️

20,190 görüntüleme • 6 ay önce

Claude Code Templates is now part of the Neon Postgres Open Source Program. One command to get a full Postgres setup for Claude Code. What you get: - 2 Skills (instant Postgres provisioning + best practices) - 5 Agents (schema design, auth, migrations, optimization, general) - 1 MCP (Neon management API) - 2 Statuslines (dev metrics + resource monitoring) 10 components with one command. Neon Database expert ready in 5 seconds
0:27

Claude Code Templates is now part of the Neon Postgres Open Source Program. One command to get a full Postgres setup for Claude Code. What you get: - 2 Skills (instant Postgres provisioning + best practices) - 5 Agents (schema design, auth, migrations, optimization, general) - 1 MCP (Neon management API) - 2 Statuslines (dev metrics + resource monitoring) 10 components with one command. Neon Database expert ready in 5 seconds

Daniel San

12,443 görüntüleme • 7 ay önce

Introducing - your AI powered Data Scientist - connect a data source (Google Sheets, Excel, Postgres Database) - analyze and transform data - generate insights - create visualizations follow for more updates
0:27

Introducing - your AI powered Data Scientist - connect a data source (Google Sheets, Excel, Postgres Database) - analyze and transform data - generate insights - create visualizations follow for more updates

rahul

324,422 görüntüleme • 3 yıl önce

With PGlite + Electric sync you can build an issue tracker handling 100k issues + 500k comments, synced from Postgres to PGlite in the browser! Super fast UI updates with all writes going though the local database, and Postgres FTS in PGlite for search 🔥
1:13

With PGlite + Electric sync you can build an issue tracker handling 100k issues + 500k comments, synced from Postgres to PGlite in the browser! Super fast UI updates with all writes going though the local database, and Postgres FTS in PGlite for search 🔥

Sam Willis

55,412 görüntüleme • 1 yıl önce

DBngin is such a good little app for managing database local DB servers. Highly recommended if your app needs a MySQL, Postgres or Redis DB
0:39

DBngin is such a good little app for managing database local DB servers. Highly recommended if your app needs a MySQL, Postgres or Redis DB

Wes Bos

85,397 görüntüleme • 1 yıl önce

How Postgres 17 improves IN queries In prior releases, postgres would loop and do multiple "primitive" index scans as many as your IN elements. In Postgres 17 it takes an array and eliminates the need for multiple scans. This only applies for constant values
3:39

How Postgres 17 improves IN queries In prior releases, postgres would loop and do multiple "primitive" index scans as many as your IN elements. In Postgres 17 it takes an array and eliminates the need for multiple scans. This only applies for constant values

Hussein Nasser

143,562 görüntüleme • 1 yıl önce

MySQL vs Postgres: storage engine addition. Clustered indexes (MySQL) and heap tables (Postgres) each have unique advantages. Covered the differences and practical implications in the latest stream.
13:46

MySQL vs Postgres: storage engine addition. Clustered indexes (MySQL) and heap tables (Postgres) each have unique advantages. Covered the differences and practical implications in the latest stream.

Ben Dicken

19,991 görüntüleme • 3 ay önce

Postgres databases now come with LLM-powered index recommendations. Indexes are crucial for database performance, and these recommendations help ensure your queries are executing optimally.
7:48

Postgres databases now come with LLM-powered index recommendations. Indexes are crucial for database performance, and these recommendations help ensure your queries are executing optimally.

PlanetScale

38,328 görüntüleme • 9 ay önce

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!
0:45

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!

Tyler Shukert

203,451 görüntüleme • 1 yıl önce

Setting up a database shouldn't take longer than writing the app. Node + Postgres in one deployment. Done in 30 seconds.
0:24

Setting up a database shouldn't take longer than writing the app. Node + Postgres in one deployment. Done in 30 seconds.

Kova

22,120 görüntüleme • 7 ay önce

Postgres: process-per-connection MySQL: thread-per-connection Learn more about processes, threads, connection pooling, and how they impact database performance in our latest interactive article.
0:34

Postgres: process-per-connection MySQL: thread-per-connection Learn more about processes, threads, connection pooling, and how they impact database performance in our latest interactive article.

PlanetScale

349,579 görüntüleme • 11 ay önce

We re-architected Neon Auth to integrate it directly into the Neon platform. Auth now lives in your Postgres database and branches with your data. Built on Better Auth tech and available today 🧵
1:12

We re-architected Neon Auth to integrate it directly into the Neon platform. Auth now lives in your Postgres database and branches with your data. Built on Better Auth tech and available today 🧵

Neon Postgres

35,061 görüntüleme • 8 ay önce

Introducing Supabase Pipelines. Your app runs on Postgres, but your analytics usually live somewhere else, like BigQuery. Pipelines keeps that data in sync for you in near real time, with no pipeline to build or maintain.
0:36

Introducing Supabase Pipelines. Your app runs on Postgres, but your analytics usually live somewhere else, like BigQuery. Pipelines keeps that data in sync for you in near real time, with no pipeline to build or maintain.

Supabase

63,051 görüntüleme • 1 ay önce

Just Use Postgres feat. Denis Magda Denis literally just published a book called “Just Use Postgres”. In this conversation, that turned out to be super fun, we talked about: • what MySQL got wrong w.r.t community • the recent explosion of Postgres development in the world (Supabase, Neon, Crunchy, ClickHouse) • when Postgres instead of Kafka • the significance of the meme “just use postgres” • Postgres for data analytics Chapters (00:00) Intro (04:26) The Just Use Postgres Movement (08:36) The Small Data Trend and Its Implications (15:49) The Shift from Distributed Systems to Simplicity (17:15) Updating your priors re: PG capabilities (20:28) MySQL's OSS community split & our experiences with such things (39:48) Postgres for Analytics (55:49) PG in the lake house (59:27) AI Marketing Slop (01:02:19) How you'd build a brand new app on Postgres (01:05:24) Speedrun through PG extensions (01:11:56) PG as a Message Queue
1:30:33

Just Use Postgres feat. Denis Magda Denis literally just published a book called “Just Use Postgres”. In this conversation, that turned out to be super fun, we talked about: • what MySQL got wrong w.r.t community • the recent explosion of Postgres development in the world (Supabase, Neon, Crunchy, ClickHouse) • when Postgres instead of Kafka • the significance of the meme “just use postgres” • Postgres for data analytics Chapters (00:00) Intro (04:26) The Just Use Postgres Movement (08:36) The Small Data Trend and Its Implications (15:49) The Shift from Distributed Systems to Simplicity (17:15) Updating your priors re: PG capabilities (20:28) MySQL's OSS community split & our experiences with such things (39:48) Postgres for Analytics (55:49) PG in the lake house (59:27) AI Marketing Slop (01:02:19) How you'd build a brand new app on Postgres (01:05:24) Speedrun through PG extensions (01:11:56) PG as a Message Queue

Stanislav Kozlovski

13,036 görüntüleme • 7 ay önce