--- title: Build Powerful Tables. Ship Faster. | daily.dev description: A deep dive into the architecture of react-table-craft, a high-performance React data grid library. Covers the headless-first design separating core state... canonical: https://daily.dev/posts/build-powerful-tables-ship-faster--9ooenzgqi twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Build Powerful Tables. Ship Faster. | daily.dev og:description: A deep dive into the architecture of react-table-craft, a high-performance React data grid library. Covers the headless-first design separating core state... og:url: https://daily.dev/posts/build-powerful-tables-ship-faster--9ooenzgqi og:image: https://api.daily.dev/og/posts/9OOEnzgqI.png og:image:alt: Build Powerful Tables. Ship Faster. og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Build Powerful Tables. Ship Faster. **[All ShadCN](https://daily.dev/sources/allshadcn)** · [@khdrawy](https://daily.dev/khdrawy) · 4 min read · 162 upvotes · 5 comments ## Summary A deep dive into the architecture of react-table-craft, a high-performance React data grid library. Covers the headless-first design separating core state engine from UI, a multi-layer config merging system to avoid prop explosion, virtualization as a first-class feature, strict TypeScript generics throughout, and built-in i18n/RTL support at the state level. Also shares performance targets (sub-16ms render for 1k rows, 100k+ row virtualization, <8KB gzipped core) and lessons learned about treating tables as systems rather than components. ## Content ## Building a High-Performance, Fully Typed React Data Grid — Architecture, Tradeoffs, and Lessons [Documentation](https://react-table-craft.vercel.app/docs) [NPM](https://www.npmjs.com/package/react-table-craft/access) [GitHub](https://github.com/Ahmed-Elkhdrawy/table-craft) Data tables look simple — until they aren’t. In real production dashboards, tables quickly become the most complex UI surface in the entire system. Once you combine virtualization, server-side data, filtering, sorting, URL state sync, accessibility, i18n, and RTL layouts — you’re no longer building a component. You’re building infrastructure. This post walks through how I designed a modern React data grid focusing on performance, type safety, extensibility, and global-ready UI. ## The Real Problem with Most Table Libraries Most libraries optimize for one of three things: ### 1️⃣ Simplicity Great DX, but breaks at scale. ### 2️⃣ Feature Power Massive feature set, but: - Hard to customize - Heavy bundle size - Steep learning curve ### 3️⃣ UI-first Design Looks good, but logic is tightly coupled to rendering. I wanted something different: - Headless-first architecture - Fully typed API surface - Config-driven feature system - Built-in global readiness (i18n + RTL) - Performance predictable at scale ## Core Architectural Principles ### Headless Core + Styled Shell Instead of shipping a monolithic component: ``` core/ state engine feature engine data pipeline react/ hooks adapters ui/ styled components (shadcn + tailwind) ``` This separation allowed: - UI swapping - Custom renderers - Framework portability - Easier testing ### Config Layering System One of the hardest problems in reusable UI infrastructure is override strategy. I implemented multi-layer config merging: ``` Global Config ↓ Provider Config ↓ Instance Config ↓ Feature Config ``` This enables: - Enterprise default behavior - Per-product overrides - Per-table customization - Feature-level fine control Without prop explosion. ## Performance Strategy ### Virtualization First — Not Optional Instead of making virtualization a plugin, it’s core behavior. Goals: - Constant DOM node count - Predictable memory usage - Stable FPS during scroll ### Render Minimization Strategy Key decisions: - Column definitions are memoized - Feature state isolated by module - Derived state cached via selectors - Stable callback references Target: Zero unnecessary re-renders. ### Data Pipeline Design ``` Raw Data → Server Adapter → Feature Transforms → Row Model → Virtual Window → Renderer ``` Each step is isolated and testable. ## Type System Design Strict generics across: - Row data model - Column definitions - Filter models - Sorting model - API adapters Example design philosophy: If it can be typed — it must be typed. Result: Autocomplete becomes documentation. ## i18n and RTL — Built Into State, Not UI Common mistake: Translation handled only in UI layer. Instead: - Locale affects formatting logic - Direction affects layout calculations - State is locale-stable - Language switch doesn’t remount table ## Feature Flag Architecture Features are modular: - Sorting - Filtering - Selection - Export - Column visibility - Search - Floating actions Each feature registers: - State slice - Reducers - Selectors - UI bindings ## Performance Targets - Initial render (1k rows): < 16ms - Virtualized datasets: 100k+ rows - Bundle goal: < 8KB gzipped core - DOM nodes: visible rows only ## Lessons Learned ### Tables Are Systems, Not Components If you don’t design them like systems, they collapse under product growth. ### Type Safety Multiplies Value Over Time The bigger the codebase, the more generics pay off. ### Config > Props Props scale poorly in infrastructure components. ## What I’d Do Differently If starting today: - Build plugin API earlier - Add DevTools from day one - Ship performance profiling hooks built-in ## Final Thought The moment your product depends on data — your table stops being UI. It becomes architecture. If you’re building something similar, I’d love to hear: What’s been the hardest part of scaling tables in production? ## Community discussion Top comments from developers on daily.dev. **@jacksonkasi** · 5 upvotes > Hey, this is really awesome. I’m surprised by how similar our ideas are—even the name. > > I’m also building the same thing you’re working on, but with a different approach. (backend + front-end - work with both or independently) > > **🚀 Drizzle table query builder engine + Shadcn + Airtable = Complex table setup in 5 minutes instead of 1 hour.** > > I’ve covered almost everything you mentioned, so I’ll be finishing my version as well. > > I really appreciate open-source builders like you who contribute to the community.... **@apperside** · 4 upvotes > There is an elephant in the room here that has not been mentioned: accessibility. > > In data grid, that is going to be a really big pain in the ass!! **@nihadd** · 1 upvotes > Looks good 😎 ## Similar posts on daily.dev - [Medium](https://daily.dev/posts/medium-3pxcxwtng) · Medium · 0 upvotes · 0 comments - [Issue \#462: Building bulletproof React components and handling billion-row tables — React Status](https://daily.dev/posts/issue-462-building-bulletproof-react-components-and-handling-billion-row-tables-react-status-dzcgnjyax) · React Status · 0 upvotes · 0 comments - [Build a headless table engine in Vue 3](https://daily.dev/posts/build-a-headless-table-engine-in-vue-3-nbnigh8la) · LogRocket · 4 upvotes · 0 comments - [Build Fast, Scalable React Data Grids for Large Datasets Using Virtualization \[Webinar Show Notes\]](https://daily.dev/posts/build-fast-scalable-react-data-grids-for-large-datasets-using-virtualization-webinar-show-notes--grkoxcqia) · Syncfusion · 1 upvotes · 0 comments --- Tags: [#react](https://daily.dev/tags/react), [#performance](https://daily.dev/tags/performance), [#infrastructure](https://daily.dev/tags/infrastructure), [#typescript](https://daily.dev/tags/typescript) [View this post on daily.dev](https://daily.dev/posts/build-powerful-tables-ship-faster--9ooenzgqi) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/build-powerful-tables-ship-faster--9ooenzgqi","headline":"Build Powerful Tables. 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Also shares performance targets (sub-16ms render for 1k rows, 100k+ row virtualization, <8KB gzipped core) and lessons learned about treating tables as systems rather than components.","url":"https://daily.dev/posts/build-powerful-tables-ship-faster--9ooenzgqi","datePublished":"2026-02-23T05:38:54.179Z","dateModified":"2026-02-23T05:39:12.909Z","author":{"@type":"Person","name":"Ahmed Elkhdrawy","url":"https://daily.dev/khdrawy","image":"https://lh3.googleusercontent.com/a/ACg8ocJ0TR8beW8YvbyKcFl_fKMaaFf632uBJ0zi7-cjz9Qwz6jlimqd=s96-c","interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"EndorseAction"},"userInteractionCount":220}},"image":"https://media.daily.dev/image/upload/s--0J-NEfkY--/f_auto/v1771800127/posts/isJLYC7fa?_a=BAMAMiiu0","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":162},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":5}],"comment":[{"@type":"Comment","text":"Hey, this is really awesome. I’m surprised by how similar our ideas are—even the name.\nI’m also building the same thing you’re working on, but with a different approach. (backend + front-end - work with both or independently)\n🚀 Drizzle table query builder engine + Shadcn + Airtable = Complex table setup in 5 minutes instead of 1 hour.\nI’ve covered almost everything you mentioned, so I’ll be finishing my version as well.\nI really appreciate open-source builders like you who contribute to the community. 🔥\nhttps://github.com/jacksonkasi1/TableCraft?tab=readme-ov-file","datePublished":"2026-02-24T15:32:52.784Z","url":"https://daily.dev/posts/9OOEnzgqI#c-oEk2UCike","author":{"@type":"Person","name":"Jackson Kasi","url":"https://daily.dev/jacksonkasi","image":"https://media.daily.dev/image/upload/s--XxJiS3vQ--/f_auto/v1709450241/avatars/avatar_Xc3cPtMNDMZMGhB0cVbSi"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":5}},{"@type":"Comment","text":"There is an elephant in the room here that has not been mentioned: accessibility.\nIn data grid, that is going to be a really big pain in the ass!!","datePublished":"2026-02-26T05:07:19.906Z","url":"https://daily.dev/posts/9OOEnzgqI#c-JIFokdOAK","author":{"@type":"Person","name":"Apperside","url":"https://daily.dev/apperside","image":"https://avatars.githubusercontent.com/u/5955338?v=4"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":4}},{"@type":"Comment","text":"Looks good 😎","datePublished":"2026-03-05T17:06:32.099Z","url":"https://daily.dev/posts/9OOEnzgqI#c-JQB7TrtQ2","author":{"@type":"Person","name":"Nego","url":"https://daily.dev/nihadd","image":"https://avatars.githubusercontent.com/u/61694826?v=4"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}}],"isPartOf":{"@type":"WebPage","url":"https://daily.dev/squads/allshadcn","name":"All ShadCN"}} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"All ShadCN","item":"https://daily.dev/squads/allshadcn"},{"@type":"ListItem","position":3,"name":"Build Powerful Tables. 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