Redux vs TanStack Query: Choosing the Right Tool for Client and Server State

🚀 We stopped using Redux for server state — and built everything on TanStack Query instead. In a large Next.js 15 + React 19 app, this architecture scaled surprisingly well. Here’s what worked 👇 🏭 Query factories > raw hooks We wrapped useQuery / useInfiniteQuery into small factories. → Consistent query keys → Easy cache updates (setQueryData) → Simple invalidation No more scattered queryKey arrays across the codebase. 💾 Selective cache persistence (not everything!) Only important queries are saved to IndexedDB using a marker in the key. → No bloated cache → Fully controlled persistence ♾️ Virtual + infinite scrolling (game changer) We combined infinite queries with virtualization. 👉 The key idea: The virtualizer decides what to fetch — not the UI. This made large tables and kanban boards feel instant, even with thousands of rows. 📊 Reusable table layer Our table doesn’t care about data type. We inject a hook that returns paginated data. → Same table works for users, pipelines, or anything else → Clean separation of UI and data logic 🔄 Real-time updates without refetching WebSocket events directly update the cache using setQueryData. → UI updates instantly → No polling → One single source of truth 🔑 Simple invalidation We created a small utility with named invalidation helpers. → No one remembers query keys → Mutations stay clean 💡 Big takeaway Server state does NOT need Redux. TanStack Query already solves caching, syncing, and real-time updates — you just need to structure it well. #TanStack #ReactQuery #NextJS #React #Frontend #WebDev #JavaScript #TypeScript

Today I learned about performance optimization and data fetching in React using Code Splitting, Lazy Loading, Suspense, and React Query (TanStack Query). ** Code Splitting Code splitting helps break large bundles into smaller chunks, so the app loads faster and only required code is loaded when needed. ** React.lazy() It allows us to load components dynamically instead of loading everything at once. const Home = React.lazy(() => import("./Home")); ** Suspense & Fallback Suspense is used with lazy loading to show a fallback UI (like a loader) while the component is loading. <Suspense fallback={<h2>Loading...</h2>}> <Home /> </Suspense> ** React Query (TanStack Query) React Query helps in fetching, caching, and managing server data efficiently. It automatically handles API caching, loading states, and background updates. @Devendra Dhote @Ritik Rajput @Mohan Mourya @Suraj Mourya #ReactJS #WebDevelopment #FullStackDeveloper #CodingJourney

I wrote 50 lines of fetch code last week. TanStack Query did the same job in 5 lines. 🤯 Here's the truth: Most React devs still write data fetching like this: - useState for data - useState for loading - useState for error - useEffect to fetch - Manual error handling - Manual loading checks That's 50+ lines for ONE API call. TanStack Query does it in 5 lines. Plus you get for FREE: ✅ Auto caching — no duplicate API calls ✅ Auto retry — when requests fail ✅ Auto refetch — when user comes back to tab ✅ Background updates — no UI flicker ✅ Less code — less bugs I was reinventing the wheel for 2 years. TanStack Query had already solved it. If you're building a real app with users, you NEED: - Caching - Retry logic - Stale data handling You can write all this manually. Or you can use TanStack Query and ship faster. Quick start: 1. npm install @tanstack/react-query 2. Wrap app in QueryClientProvider 3. Replace useEffect with useQuery 4. Done. Honest question for React devs: Are you still fetching with useState + useEffect? What's stopping you from switching? 👇 #ReactJS #FrontendDevelopment #JavaScript #TanStackQuery #ReactQuery #WebDevelopment #ReactDeveloper #NextJS #SoftwareEngineering #TechTips

🚀 Exploring React’s cache() — A Hidden Performance Superpower Most developers focus on UI optimization… But what if your data fetching could be smarter by default? Recently, I explored the cache() utility in React — and it completely changed how I think about data fetching in Server Components. 💡 What’s happening here? Instead of calling the same API multiple times across components, we wrap our function with: import { cache } from 'react'; const getCachedData = cache(fetchData); Now React automatically: ✅ Stores the result of the first call ✅ Reuses it for subsequent calls ✅ Avoids unnecessary duplicate requests ⚡ Why this matters Imagine multiple components requesting the same data: Without caching → Multiple API calls ❌ With cache() → One call, shared result ✅ This leads to: Better performance Reduced server load Cleaner and more predictable data flow 🧠 The real beauty You don’t need: External caching libraries Complex state management Manual memoization React handles it for you — elegantly. 📌 When to use it? Server Components Reusable data-fetching logic Expensive or repeated API calls 💬 Takeaway Modern React is not just about rendering UI anymore — it’s becoming a data-aware framework. And features like cache() prove that the future is about writing less code with smarter behavior. #ReactJS #WebDevelopment #PerformanceOptimization #JavaScript #FrontendDevelopment #FullStack #ReactServerComponents #CodingTips #SoftwareEngineering

🚀 Stop treating Server State like UI State. As React developers, we’ve all been there: building "custom" fetching logic with useEffect and useState. It starts with one loading spinner and ends with a nightmare of manual cache-busting and race conditions. When I started migrating my data-fetching to TanStack Query, it wasn't just about "fewer lines of code"—it was about a shift in mindset. The Real Game Changers: Declarative vs. Imperative: Instead of telling React how to fetch (and handle errors/loading), you describe what the data is and when it should be considered stale. Focus Refetching: This is a huge UX win. Seeing data update automatically when a user switches back to the tab feels like magic to them, but it’s just one config line for us. Standardized Patterns: It forces the whole team to handle errors and loading states the same way, which makes code reviews much faster. The Win: In a recent refactor, I replaced a tangled mess of global state syncs and manual useEffect triggers with a few useQuery hooks. I was able to delete a significant chunk of boilerplate while fixing those "stale data" bugs that always seem to haunt client-side apps. The takeaway: Don't reinvent the cache. Use tools that let you focus on the product, not the plumbing. 👇 Question for the devs: Are you using TanStack Query for everything, or are you finding that Next.js Server Actions and the native fetch cache are enough for your use cases now? #reactjs #nextjs #frontend #webdev #tanstackquery #javascript

🔥 Stop Making Repeated API Calls in React! (Use Smart Caching) As a Frontend Developer, one of the most common performance issues I’ve seen is: 👉 Same API getting called again and again This not only slows down the app ⏳ but also increases server load 📉 💡 The solution? Client-Side Caching using TanStack Query (React Query) --- ✅ What is TanStack Query? It’s a powerful data-fetching library that automatically: ✔️ Caches API responses ✔️ Prevents duplicate API calls ✔️ Refetches data in background ✔️ Manages loading & error states --- 💻 Example: Avoid Redundant API Calls import { useQuery } from "@tanstack/react-query"; const fetchUsers = async () => { const res = await fetch("/api/users"); return res.json(); }; export default function Users() { const { data, isLoading } = useQuery({ queryKey: ["users"], // unique cache key queryFn: fetchUsers, staleTime: 5 * 60 * 1000, // cache valid for 5 mins }); if (isLoading) return <p>Loading...</p>; return <div>{data.length} users</div>; } --- 🧠 How it works? - First API call → data stored in cache - Next time → data served from cache (no API call) 🚀 - After "staleTime" → background refetch happens --- ⚡ Why I prefer this in production? 👉 No need to manually manage cache 👉 Built-in request deduplication 👉 Improves performance drastically 👉 Cleaner & scalable code --- 🎯 Pro Tip (Senior Level) Use proper "queryKey" + cache invalidation strategy for dynamic apps --- 💬 Have you used React Query or still managing API calls manually? Let’s discuss 👇 #ReactJS #Frontend #Performance #WebDevelopment #JavaScript #ReactQuery #TanStackQuery #SoftwareEngineering

Last week I deployed what looked like a perfect product page. Then a client screenshot landed in my inbox… 👉 Prices from 3 days ago. The database had the correct data. The API returned the correct data. But the page? ❌ Completely frozen in time. 🚨 What was actually happening? Next.js App Router silently overrides the native fetch() API. By default, every request runs with: 👉 cache: 'force-cache' That means: Data is cached permanently Stored on disk And ignores your HTTP Cache-Control headers 🤯 The real complexity There isn’t just one cache layer — there are four: Request Memoization Data Cache Full Route Cache Router Cache 👉 Which makes debugging stale data extremely tricky 👉 Especially when everything works fine locally ✅ How to fix it properly ✔ Always define your caching strategy explicitly ✔ Use revalidate for controlled updates ✔ Call revalidatePath() or revalidateTag() after mutations ✔ Use cache: 'no-store' only for real-time or user-specific data ✔ Tag your fetches — it’s the most scalable approach 🔑 Key Takeaways Next.js fetch() defaults to permanent caching Dev mode does NOT reflect production caching behavior Stale data bugs usually appear after deployment Proper cache control = predictable apps Bookmark this. Your future self will thank you when your client sends another screenshot. 🔖 💬 What’s the worst caching bug you’ve faced in Next.js? #NextJS #WebDev #React #TypeScript #JavaScript #Frontend #FullStack #SoftwareDevelopment #Programming #TechTips

🚀 Why You Should Use React Query (TanStack Query) in Your Next Project If you're still managing server state manually with useEffect + useState… you're making life harder than it needs to be. Here’s why React Query is a game-changer 👇 🔹 1. Smart Data Fetching React Query handles caching, background updates, and synchronization automatically — no need to write repetitive API logic. 🔹 2. Built-in Caching Data is cached by default, which means faster UI and fewer unnecessary API calls. 🔹 3. Automatic Refetching It can refetch data in the background when the window refocuses or network reconnects. 🔹 4. Easy Loading & Error States No more manual flags — React Query gives you clean states like isLoading, isError, isSuccess out of the box. 🔹 5. Pagination & Infinite Scroll Handling pagination becomes super simple with built-in support. 🔹 6. Better Developer Experience Cleaner code, less boilerplate, and improved maintainability. 💡 In short: React Query lets you focus on building features instead of managing server state. Have you tried React Query yet? Share your experience 👇 #ReactJS #WebDevelopment #Frontend #JavaScript #Programming #Developers #Tech

🚀 Why I Stopped Putting "Server State" in Redux If you’ve spent years building React apps, you know the struggle: your Redux store becomes a massive "junk drawer" of API data, loading booleans, and error strings. Then came TanStack Query. It changed the game by introducing a simple but powerful distinction: 𝗰𝗹𝗶𝗲𝗻𝘁 𝘀𝘁𝗮𝘁𝗲 vs. 𝘀𝗲𝗿𝘃𝗲𝗿 𝘀𝘁𝗮𝘁𝗲. 🔍 The Core Shift Most of what we store in Redux isn't actually "state"—it's a 𝗰𝗮𝗰𝗵𝗲 𝗼𝗳 𝗿𝗲𝗺𝗼𝘁𝗲 𝗱𝗮𝘁𝗮. • 𝗥𝗲𝗱𝘂𝘅/𝗭𝘂𝘀𝘁𝗮𝗻𝗱 is for things you own (Theme, Modals, Form inputs). • 𝗧𝗮𝗻𝗦𝘁𝗮𝗰𝗸 𝗤𝘂𝗲𝗿𝘆 is for things the server owns (User profiles, Product lists, Dashboard stats). 🛠️ How it manages data (without the boilerplate): 1️⃣ The Global Cache (QueryClient): Think of it as an invisible, self-managing store. You don’t write reducers; the QueryClient automatically handles the storage of every API response. 2️⃣ Query Keys = Selectors: By using a unique key like ['users', userId], any component in your app can access that data. If Component A and Component B call the same key, TanStack Query ensures only one network request is made. 3️⃣ Stale-While-Revalidate (SWR): This is the "magic." It shows users cached (stale) data immediately so the UI feels instant, then fetches the fresh data in the background. 💡 The Result? By moving server-side logic to TanStack Query, I’ve seen codebases shrink by 30-40%. No more manual useEffect for fetching, no more redundant loading variables, and no more bloated stores. Are you still using Redux for API data, or have you made the switch? Let's discuss! 👇 #ReactJS #WebDevelopment #TanStackQuery #Redux #Frontend #SoftwareEngineering #ProgrammingTips #WebDev

React Performance Tip: Stop Overusing useEffect — Use useQuery Instead One mistake I often see (and made myself earlier) while working with React apps is overusing useEffect for API calls. 👉 Typical approach: Call API inside useEffect Manage loading state manually Handle errors separately Re-fetch logic becomes messy This works… but it doesn’t scale well. 🔁 Better approach: Use React Query (useQuery) When I started using useQuery, it simplified a lot of things: ✅ Automatic caching ✅ Built-in loading & error states ✅ Background refetching ✅ Cleaner and more readable code 👉 Example: Instead of this 👇 useEffect(() => { setLoading(true); axios.get('/api/data') .then(res => setData(res.data)) .catch(err => setError(err)) .finally(() => setLoading(false)); }, []); Use this 👇 const { data, isLoading, error } = useQuery({ queryKey: ['data'], queryFn: () => axios.get('/api/data').then(res => res.data), }); 🔥 Result: Less boilerplate Better performance (thanks to caching) Easier state management 📌 Takeaway: If you're building scalable React applications, tools like React Query are not optional anymore — they’re essential. What’s one React optimization you swear by? Drop it in the comments 👇 #ReactJS #WebDevelopment #Frontend #JavaScript #SoftwareEngineering #CleanCode #TechTips #Developers