Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

The Spring Data Team JDBC framework does not support schema generation yet: But there is a workaround! Use IntelliJ IDEA to generate schema init scripts for Liquibase and Flyway.

intellijidea's profile picture

IntelliJ IDEA, a JetBrains IDE

157,578 subscribers

14,478 görüntüleme • 6 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Teams often start model-first, then switch to DB-first (or the other way around) 😅 Syncing both worlds manually is painful. Spring Data JDBC supports both approaches, and IntelliJ IDEA generates DB schema from entities and entities from schema 🔄
0:29

Teams often start model-first, then switch to DB-first (or the other way around) 😅 Syncing both worlds manually is painful. Spring Data JDBC supports both approaches, and IntelliJ IDEA generates DB schema from entities and entities from schema 🔄

IntelliJ IDEA, a JetBrains IDE

14,817 görüntüleme • 6 ay önce

As Spring Data JDBC is gaining popularity, IntelliJ IDEA 2025.3 brings first-class support on par with its support for Spring Data JPA. Learn more 👉
1:11

As Spring Data JDBC is gaining popularity, IntelliJ IDEA 2025.3 brings first-class support on par with its support for Spring Data JPA. Learn more 👉

IntelliJ IDEA, a JetBrains IDE

35,592 görüntüleme • 8 ay önce

this is super cool. there's a feature in an upcoming JetBrains IntelliJ IDEA, a JetBrains IDE that lets you trivially reverse engineer a schema into JPA entities. I've been assured that they're working on Spring Data Team JDBC support, too! // paging my friend Aleksey Stukalov come and see more today at #intellijideaconf 2025 !
1:04

this is super cool. there's a feature in an upcoming JetBrains IntelliJ IDEA, a JetBrains IDE that lets you trivially reverse engineer a schema into JPA entities. I've been assured that they're working on Spring Data Team JDBC support, too! // paging my friend Aleksey Stukalov come and see more today at #intellijideaconf 2025 !

Josh Long

11,551 görüntüleme • 1 yıl önce

📣 Announcing: KickStart! A next-generation form builder from the FormKit team. Going live...now 👀 Generate a form, edit it with manual controls or AI prompts, then copy and paste Vue components or schema into your project. 🔗👇
0:52

📣 Announcing: KickStart! A next-generation form builder from the FormKit team. Going live...now 👀 Generate a form, edit it with manual controls or AI prompts, then copy and paste Vue components or schema into your project. 🔗👇

Justin Schroeder

41,004 görüntüleme • 2 yıl önce

Agentic Document Extraction now supports field extraction! Many doc extraction use cases extract specific fields from forms and other structured documents. You can now input a picture or PDF of an invoice, request the vendor name, item list, and prices, and get back the extracted fields. Or input a medical form and specify a schema to extract patient name, patient ID, insurance number, etc. One cool feature: If you don't feel like writing a schema (json specification of what fields to extract) yourself, upload one sample document and write a natural language prompt saying what you want, and we automatically generate a schema for you. See the video for details!
3:16

Agentic Document Extraction now supports field extraction! Many doc extraction use cases extract specific fields from forms and other structured documents. You can now input a picture or PDF of an invoice, request the vendor name, item list, and prices, and get back the extracted fields. Or input a medical form and specify a schema to extract patient name, patient ID, insurance number, etc. One cool feature: If you don't feel like writing a schema (json specification of what fields to extract) yourself, upload one sample document and write a natural language prompt saying what you want, and we automatically generate a schema for you. See the video for details!

Andrew Ng

193,139 görüntüleme • 1 yıl önce

Building on Solana just got easier. HyperStack joins your onchain accounts any way you want and streams the data straight to you. Just define a single schema. Our infra does the rest. Join the waitlist 👇
0:38

Building on Solana just got easier. HyperStack joins your onchain accounts any way you want and streams the data straight to you. Just define a single schema. Our infra does the rest. Join the waitlist 👇

HyperTek

95,200 görüntüleme • 10 ay önce

CubePart is the latest update to our open-source Cube 3D foundation model. It lets creators pair a text prompt with an open-ended part schema to generate labeled meshes that drop straight into a game engine for physics, animation, and scripting.
0:35

CubePart is the latest update to our open-source Cube 3D foundation model. It lets creators pair a text prompt with an open-ended part schema to generate labeled meshes that drop straight into a game engine for physics, animation, and scripting.

David Baszucki

143,159 görüntüleme • 3 ay önce

Nile Feature Unboxing 🎁 🎉 Introducing Nile’s schema visualizer. Nile console now includes a built-in schema visualizer. Making it easy to grok the data models of your SaaS and iterate as a team. Nile feature unboxing is a day dedicated to a new feature. We will be sharing content about the feature through out the day: 11:00 am PST - Video tutorial 1:00 pm PST - Technical blog on how we built it 3:00 pm PST - Docs and templates on how to get started
0:38

Nile Feature Unboxing 🎁 🎉 Introducing Nile’s schema visualizer. Nile console now includes a built-in schema visualizer. Making it easy to grok the data models of your SaaS and iterate as a team. Nile feature unboxing is a day dedicated to a new feature. We will be sharing content about the feature through out the day: 11:00 am PST - Video tutorial 1:00 pm PST - Technical blog on how we built it 3:00 pm PST - Docs and templates on how to get started

Gwen (Chen) Shapira

18,623 görüntüleme • 2 yıl önce

JSON columns in Postgres can be flexible, but too much flexibility can be risky as you might accidentally end up with malformed data. You can prevent this using the pg_jsonschema extension to easily define a schema for your JSON and JSONB columns!
6:25

JSON columns in Postgres can be flexible, but too much flexibility can be risky as you might accidentally end up with malformed data. You can prevent this using the pg_jsonschema extension to easily define a schema for your JSON and JSONB columns!

Tyler Shukert

17,480 görüntüleme • 1 yıl önce

I am 14, and I built (not ready to launch) an MVP called Vidmirror. It is a tool for YouTubers to find viral videos, and it can even generate thumbnails, titles, and scripts (coming soon). Not ready to launch yet because I want to do payment verification before launching it. It is still in MVP stage I am trying to add automation features and video generation. It is very easy to use, and here is the demo. i know the voice and video looks bad .don't care it
3:40

I am 14, and I built (not ready to launch) an MVP called Vidmirror. It is a tool for YouTubers to find viral videos, and it can even generate thumbnails, titles, and scripts (coming soon). Not ready to launch yet because I want to do payment verification before launching it. It is still in MVP stage I am trying to add automation features and video generation. It is very easy to use, and here is the demo. i know the voice and video looks bad .don't care it

Shayan C

433,933 görüntüleme • 1 yıl önce

🗒️ Kotlin Notebook, a new interactive environment for JVM developers, comes bundled in IntelliJ IDEA 2025.1 – both Community Edition and Ultimate. It is also coming soon to Android Studio. Experiment, prototype, visualize data, and more!
0:43

🗒️ Kotlin Notebook, a new interactive environment for JVM developers, comes bundled in IntelliJ IDEA 2025.1 – both Community Edition and Ultimate. It is also coming soon to Android Studio. Experiment, prototype, visualize data, and more!

Kotlin by JetBrains

10,838 görüntüleme • 1 yıl önce

Today at Yoast we’re shipping something I've actually wanted to see on the web for some time (even before working at Yoast) and am now honored to be part of the team to bring this to the masses... Built in collaboration with the Open Source and NLWeb team at Microsoft lead by R.V.Guha (co-creator of RSS, RDF and other web standards) - we're introducing the Schema Aggregation feature: a "schemamap" endpoint that outputs your site's entire structured data map in one place. ​ Under the hood, we now provide a standardised, deduplicated map of your entities via a single endpoint. An agent no longer needs to crawl all individual pages to understand its meaning but can now ingest an entire entity map with ease. ​ A few details to note about the endpoint: - It's is cacheable with sub‑100ms responses - It respects existing privacy and indexing settings - It aggregates all indexable content without navigation noise - It merges duplicate entities so your "Author X" or "Article Y" exist as a single node instead of being re‑discovered on every URL. - If you're using one of our paid plugins that extends schema even more (such as Yoast WooCommerce SEO adds product schema) this will be populated within the endpoint too - If you already extend Yoast’s Schema API, or use partners like events or recipe plugins, their entities are pulled into the same map automatically. ​ For me, this is one of the first major ways the agentic web can ingest a site at scale, and with much more efficiency and context. It has also been so much fun to work with this alongside the team at Yoast, particularly the genius mind of Alain Schlesser. Lastly, we have also launched a schema visualisation tool to view how everything is output. You can enable this feature today with the free version of Yoast SEO.
0:29

Today at Yoast we’re shipping something I've actually wanted to see on the web for some time (even before working at Yoast) and am now honored to be part of the team to bring this to the masses... Built in collaboration with the Open Source and NLWeb team at Microsoft lead by R.V.Guha (co-creator of RSS, RDF and other web standards) - we're introducing the Schema Aggregation feature: a "schemamap" endpoint that outputs your site's entire structured data map in one place. ​ Under the hood, we now provide a standardised, deduplicated map of your entities via a single endpoint. An agent no longer needs to crawl all individual pages to understand its meaning but can now ingest an entire entity map with ease. ​ A few details to note about the endpoint: - It's is cacheable with sub‑100ms responses - It respects existing privacy and indexing settings - It aggregates all indexable content without navigation noise - It merges duplicate entities so your "Author X" or "Article Y" exist as a single node instead of being re‑discovered on every URL. - If you're using one of our paid plugins that extends schema even more (such as Yoast WooCommerce SEO adds product schema) this will be populated within the endpoint too - If you already extend Yoast’s Schema API, or use partners like events or recipe plugins, their entities are pulled into the same map automatically. ​ For me, this is one of the first major ways the agentic web can ingest a site at scale, and with much more efficiency and context. It has also been so much fun to work with this alongside the team at Yoast, particularly the genius mind of Alain Schlesser. Lastly, we have also launched a schema visualisation tool to view how everything is output. You can enable this feature today with the free version of Yoast SEO.

Alex Moss

15,372 görüntüleme • 6 ay önce

Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!
0:25

Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!

Avi Chawla

187,076 görüntüleme • 8 ay önce

Excited to more broadly share what we've been working on at Reworkd ⚡️ This past year we've fully invested in building the next generation of web agents. They're already live in production today across a handful of companies serving as the simplest way to extract web data at scale. Come to us with a list of 100s-1000s of websites + a data schema, and we'll handle the rest 🤖
0:41

Excited to more broadly share what we've been working on at Reworkd ⚡️ This past year we've fully invested in building the next generation of web agents. They're already live in production today across a handful of companies serving as the simplest way to extract web data at scale. Come to us with a list of 100s-1000s of websites + a data schema, and we'll handle the rest 🤖

asim

94,665 görüntüleme • 2 yıl önce

My friend Sybille is a human doctor and she says Valentina’s lungs are sounding a little better. Still not perfect but there is improvement for sure she said. Hank the Tank says he has no idea what’s going on but always wants to be there for moral support (2/3)
0:22

My friend Sybille is a human doctor and she says Valentina’s lungs are sounding a little better. Still not perfect but there is improvement for sure she said. Hank the Tank says he has no idea what’s going on but always wants to be there for moral support (2/3)

Niall Harbison

71,063 görüntüleme • 2 yıl önce

The future of writing database queries is not writing them at all! MongoDB just released their own MCP Server, and it quietly shifts how we interact with databases. It connects to AI tools like Claude, Cursor, or GitHub Copilot, and you can just talk to your database using natural language: → "What's the schema for the orders collection?" → "Find the top 10 users by purchase volume." → "Create a read-only DB user." No need to context switch. No need to memorize query syntax. No need to even leave your IDE. It works across MongoDB Atlas, Community, and Enterprise, and supports admin ops, schema exploration, indexing, and code generation, all via natural language. This way, you can focus on what actually matters: data modeling, app logic, and product experience. Link to the announcement in the next tweet. Thanks to #MongoDB team for partnering with me today!
0:44

The future of writing database queries is not writing them at all! MongoDB just released their own MCP Server, and it quietly shifts how we interact with databases. It connects to AI tools like Claude, Cursor, or GitHub Copilot, and you can just talk to your database using natural language: → "What's the schema for the orders collection?" → "Find the top 10 users by purchase volume." → "Create a read-only DB user." No need to context switch. No need to memorize query syntax. No need to even leave your IDE. It works across MongoDB Atlas, Community, and Enterprise, and supports admin ops, schema exploration, indexing, and code generation, all via natural language. This way, you can focus on what actually matters: data modeling, app logic, and product experience. Link to the announcement in the next tweet. Thanks to #MongoDB team for partnering with me today!

Akshay 🚀

32,084 görüntüleme • 1 yıl önce