TANSTACK
@tan_stack
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🌎 Open Source Software for the Web👨🏽💻TypeScript 👻 Headless ⚒️ Start, Router, Query, Table, DB, Form, Virtual, Pacer, Store
Earth
Joined December 2021
We just dropped a new release of TanStack AI! 🔥 We are super excited to announce that the new release supports Standard Schema and the newly released Standard JSON Schema. 🚀 Bring your own schema library to your tools and structured outputs! 😎
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🔥 NEW: Complete TanStack Start Full Course Build a Full Stack E-commerce app while learning TanStack Start w/ ✨ TanStack Start @tan_stack 🧭 TanStack Query + TanStack Form 🎨 Modern UI @tailwindcss @shadcn ☁️ PostGres DB @supabase 🪄 ORM @DrizzleORM 🛡️ Zod @colinhacks 🚀
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These cozy knitted stockings are perfect for keeping your feet warm on chilly winter nights. Whether you’re lounging around the house, watching TV, or wearing slippers or shoes, they add comfort and style to your everyday moments.
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📣 TanStack AI Alpha is here! ✨ Framework agnostic 🤖 Provider agnostic 🧠 Type safe 🔧 Isomorphic tools 🛠 Devtools 🌐 Open protocol 📦 JS, Python, PHP ⚛️ React, Solid, Vanilla 🌀 OpenAI, Anthropic, Gemini, Ollama, ++ Official blog post: 🔗⬇︎🧵
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Why is @tan_stack DB a database? It's both something new, but also very much based on the architecture of any traditional database. All the same parts are there, and data flows through it in the same way. Only difference is it can load data from anywhere...
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Just released @tan_stack Form 1.27! Comes with React Compiler fixes (for all edgecases AFAICT), React 17 compat updates, and..... The Svelte Composition API port! 🎉 https://t.co/pqFM83FYSl Try it out in your apps and let me know what you think!
tanstack.com
A common criticism of TanStack Form is its verbosity out-of-the-box. While this can be useful for educational purposes helping enforce understanding our APIs it's not ideal in production use cases....
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Alright, after trying three different preloading strategies and further optimizations, TanStack Faster can now truly match the speed of NextFaster. Experience the true speed a @tan_stack + @Cloudflare application can achieve.
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TanStack Pacer is now in Beta
Hey look at that! TanStack Pacer is in beta now! Pretty much all of the ideas I had for Pacer originally are in the library now. Now I think it's time for refinement and specialized docs. If you use Pacer, we want to hear your feedback.
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We've just shipped query driven sync for @tan_stack DB! Huge lift to get here - this is the DX I dreamed of when I started working on sync. Define where data comes from (anywhere!) as collections, and then query over those collections in your components. 🪄🎉
🚀 TanStack DB 0.5 is here with Query-Driven Sync Your component's query IS the API call. No custom endpoints. No GraphQL resolvers. Just write your query and DB figures out exactly what to fetch. Details 🧵👇
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oh yeah this is big
🚀 TanStack DB 0.5 is here with Query-Driven Sync Your component's query IS the API call. No custom endpoints. No GraphQL resolvers. Just write your query and DB figures out exactly what to fetch. Details 🧵👇
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This has been an incredibly fun project to work on! And hats off to @samwillis and @KevinDP55 who have done some real wizardry here. Queries can now be compiled into almost any sort of data loading scheme you can imagine w/ tons of built-in optimizations.
🚀 TanStack DB 0.5 is here with Query-Driven Sync Your component's query IS the API call. No custom endpoints. No GraphQL resolvers. Just write your query and DB figures out exactly what to fetch. Details 🧵👇
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@ElectricSQL @trailbase_io @powersync_ We're targeting 1.0 for December 2025. npm install @tanstack/react-db@0.5.0 Try it and share feedback in Discord or GitHub!
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Designed for your existing REST, GraphQL, or tRPC APIs. No backend migration. Bonus: Works with sync engines (@ElectricSQL , @trailbase_io , @powersync_) for real-time updates with near-zero incremental network cost.
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First query: ~100ms with targeted network request Meanwhile: Full dataset syncs in background After sync: ALL queries run in <1ms client-side Fast first paint + instant everything else.
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Multiple components, same query? ONE network request. Complex joins? Minimal batched requests. Already-loaded rows? Reused automatically. Fewer total requests than custom APIs, with better cache utilization.
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Differential dataflow recomputes only what changed. Mark a todo complete? Query results update in <1ms—even with 100k+ rows in memory. No jitter. No loading states. Just instant updates.
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0.5 adds 3 sync modes for different use cases: - Eager: Load everything upfront (<10k rows) - On-demand: Load only what queries need (>50k rows, search) - Progressive: Load subset now, sync full dataset in background (collaborative apps)
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