Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

🚀 Launched today 2.0 🐘 Modern Postgres Terminal. Fast. Native. Written in Rust. Everything you already had in the shell - now with a native TUI and PgBot built in. → SQL - write queries and inspect results → Data - browse schemas, tables and rows → Branches -... show more

alex shapalov

3,167 subscribers

66,979 views • 2 months ago •via X (Twitter)

Science & Technology

Anya Rossi• Live Now

Private livecam show

23 Comments

ActiveRabbit2 months ago

Great design!

alex shapalov2 months ago

tnx, open for contribution)

Sujal2 months ago

what pushed you to native over a tui? curious whether it was rendering speed or just wanting proper mouse support in the terminal.

alex shapalov2 months ago

it's a tui, that was a mock and terminals do mouse fine OSC 22 even gets you a real hand cursor. it needs to run over ssh, so native was never on the table)

Matt DeLuco2 months ago

You should have lead with no electron! 🎉

alex shapalov2 months ago

yee, and i lead with Rust!

alex shapalov2 months ago

Worth trying:

The Chieftain A2 months ago

Amazing

alex shapalov2 months ago

Thanks. 🙏 Some more updates will be soon

Axiom 🔬2 months ago

The safety model is the product edge here. A DB agent needs a signed query plan, row-limit, mutation gate, explain trace, and rollback handle next to the TUI. Otherwise ask your database becomes let a chatbot discover DELETE.

Alexander Holbreich2 months ago

Actualy looks like fun!

alex shapalov2 months ago

Yes, fan and useful

Christian Lempa2 months ago

That looks great

alex shapalov2 months ago

Tnx for feedback

هزيم الرعد2 months ago

is there an in terminal browser ?

alex shapalov2 months ago

A browser based terminal wouldn’t be secure

هزيم الرعد2 months ago

would be cool tho

alex shapalov2 months ago

Maybe for test db, or I am not sure about security…

pgrun.dev2 months ago

install: curl -fsSL | sh

alex shapalov2 months ago

Yes, the installation process is the same for all versions.

PuneetSingh��️2 months ago

native TUI + PgBot is a nice agent surface — curious if PgBot gets schema/table browse as tools with structured returns, or if it's still chat-over-SQL. structured row previews beat dumping query text into the context window

Leo Oliemans | Refinery2 months ago

A native Postgres terminal plus a bot sounds useful for inspection. I’d keep the mutation boundary very visible, though: read, explain, propose, then explicitly execute. Especially when the result looks plausible but the target rows changed meanwhile.

alex shapalov2 months ago

No Electron!

Related Videos

🚀 launched today: 🐘 Postgres branches for every AI agent. → build a Postgres branch in ~3 seconds → production-like data → isolated database for every agent → sensitive data automatically masked → branch → work → delete Already ~100 Postgres branches/week before public launch. Now we're building the Postgres runtime for agents.

🚀 launched today: 🐘 Postgres branches for every AI agent. → build a Postgres branch in ~3 seconds → production-like data → isolated database for every agent → sensitive data automatically masked → branch → work → delete Already ~100 Postgres branches/week before public launch. Now we're building the Postgres runtime for agents.

alex shapalov

113,130 views • 1 month ago

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 🧵

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 views • 11 months ago

🚨 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 🔥

🚨 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 🔥

Charly Wargnier ♨️

20,190 views • 9 months ago

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.

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

94,406 views • 11 months ago

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 views • 1 year ago

AI workloads need databases built for scale. Watch how OceanBase supports modern data infrastructure. Follow OceanBase for more insights on distributed SQL, cloud-native databases, and AI-ready architecture.

AI workloads need databases built for scale. Watch how OceanBase supports modern data infrastructure. Follow OceanBase for more insights on distributed SQL, cloud-native databases, and AI-ready architecture.

OceanBase

8,134,345 views • 5 months ago

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

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 views • 1 year ago

sqlit is a lazygit style SQL TUI for the terminal. It supports 10+ databases (Postgres, SQLite, Supabase, ClickHouse, DuckDB, etc), has query history, autocomplete and more. Peter Adams (Maxteabag on GitHub) made sqlit using textualize.io and is Terminal Tool of the Week! ⭐️

sqlit is a lazygit style SQL TUI for the terminal. It supports 10+ databases (Postgres, SQLite, Supabase, ClickHouse, DuckDB, etc), has query history, autocomplete and more. Peter Adams (Maxteabag on GitHub) made sqlit using textualize.io and is Terminal Tool of the Week! ⭐️

Terminal Trove

138,230 views • 10 months ago

Today ✅ : Learning PostgreSQL - learned about queries and pg library -made a simple signup page with PostgreSQL db - learned about how SQL injection works and how to prevent insert queries from it - basic relationships in postgres db Prolly need to start learning C++ too for sem exams

Today ✅ : Learning PostgreSQL - learned about queries and pg library -made a simple signup page with PostgreSQL db - learned about how SQL injection works and how to prevent insert queries from it - basic relationships in postgres db Prolly need to start learning C++ too for sem exams

Sam ☕

21,908 views • 3 months ago

YC W23's Brewit allows you to use plain English to write SQL, create charts, and generate dashboards/reports based on your database. With built-in data catalogs and monitoring tools, Brewit ensures its accuracy and capability to self-improve.

YC W23's Brewit allows you to use plain English to write SQL, create charts, and generate dashboards/reports based on your database. With built-in data catalogs and monitoring tools, Brewit ensures its accuracy and capability to self-improve.

Y Combinator

25,023 views • 2 years ago

Replit Agent (launched today) built a startup landing page with waitlist and postgres db from start to finish in <4 mins

Replit Agent (launched today) built a startup landing page with waitlist and postgres db from start to finish in <4 mins

aman

237,308 views • 2 years ago

most people stick to just 1 or 2 tables they are familiar with when writing their SQL queries in we built the ability to search for tables, preview tables and easily sample rows from a table so you can find the ones you need + even discover new tables data discovery is a big problem even in small companies. most data doesn't get analyzed because most of company doesn't know it exists

most people stick to just 1 or 2 tables they are familiar with when writing their SQL queries in we built the ability to search for tables, preview tables and easily sample rows from a table so you can find the ones you need + even discover new tables data discovery is a big problem even in small companies. most data doesn't get analyzed because most of company doesn't know it exists

rahul

11,550 views • 1 year ago

Excited to launch Data Explorer in today! 🚀 We built this to eliminate tedious data validation steps. Now you can easily inspect and validate data at each step and ask Julius to edit it - all in one place. Feedback welcome!

Excited to launch Data Explorer in today! 🚀 We built this to eliminate tedious data validation steps. Now you can easily inspect and validate data at each step and ask Julius to edit it - all in one place. Feedback welcome!

rahul

22,669 views • 1 year ago

Even the most powerful artificial minds need infrastructure to understand the world. We've launched a radical project to change the way we build AI Agents. A graph layer that uses up to 34x less RAM than neo4j. To start: pgGraph (Full Open Souce, Rust), is a postgres extension that lets you run complex graph queries, like finding shortest paths using standard SQL. Directly in postgres. Coming next: Polygres, give your postgres a warp drive by combining pgGraph & pgVector into an all-in-one database. We're building the foundation of intelligence evokoa (YCF26) Links below ↓

Even the most powerful artificial minds need infrastructure to understand the world. We've launched a radical project to change the way we build AI Agents. A graph layer that uses up to 34x less RAM than neo4j. To start: pgGraph (Full Open Souce, Rust), is a postgres extension that lets you run complex graph queries, like finding shortest paths using standard SQL. Directly in postgres. Coming next: Polygres, give your postgres a warp drive by combining pgGraph & pgVector into an all-in-one database. We're building the foundation of intelligence evokoa (YCF26) Links below ↓

dale

15,146 views • 5 months ago

SQL Studio is now in public beta 🚀 A modern, cross-platform SQL client built for speed and clarity. SQLite supported. More dialects coming. Bugs included 🪲 👉

SQL Studio is now in public beta 🚀 A modern, cross-platform SQL client built for speed and clarity. SQLite supported. More dialects coming. Bugs included 🪲 👉

Antfroze

181,835 views • 10 months ago

We built a SQL and NoSQL co-pilot: Generate an answer with accompanying code by typing a question to ask your database - built in code editor - AI sanity check - schema explorer - shareable perma-links to past queries Join the private beta here:

We built a SQL and NoSQL co-pilot: Generate an answer with accompanying code by typing a question to ask your database - built in code editor - AI sanity check - schema explorer - shareable perma-links to past queries Join the private beta here:

Use Bink

74,965 views • 3 years ago

GORI(고리) is now public! A keyboard-native TUI proxy built for pentesters and hackers. Intercept, edit, and repeat traffic right in your terminal with pure muscle memory flow. Happy Hacking in Terminal :) Github: Install:

GORI(고리) is now public! A keyboard-native TUI proxy built for pentesters and hackers. Intercept, edit, and repeat traffic right in your terminal with pure muscle memory flow. Happy Hacking in Terminal :) Github: Install:

HAHWUL

10,524 views • 3 months ago

GPT-5.6-Sol-Ultra built a Doom-like game in SQL: the game is running in the terminal on the left, while the SQL powering the game in the terminal on the right. How it works: DOOMQL is a game engine implemented in 2,000+ lines of SQL. Every frame, SQL raycasts the scene, calculates every RGB pixel, and encodes those pixels as coloured terminal characters. The same SQL then handles controls, movement, collision, enemy AI and combat, while Python connects SQLite to the keyboard, clock and terminal.

GPT-5.6-Sol-Ultra built a Doom-like game in SQL: the game is running in the terminal on the left, while the SQL powering the game in the terminal on the right. How it works: DOOMQL is a game engine implemented in 2,000+ lines of SQL. Every frame, SQL raycasts the scene, calculates every RGB pixel, and encodes those pixels as coloured terminal characters. The same SQL then handles controls, movement, collision, enemy AI and combat, while Python connects SQLite to the keyboard, clock and terminal.

Peter Gostev

122,407 views • 4 months ago