Optimizing React Performance with Code Splitting and React Query

🚀 Redux vs TanStack Query: Which One Should You Use in 2026? This is one of the most misunderstood topics in React development. Many developers compare Redux and TanStack Query as if they solve the same problem. They don’t. 👉 Redux manages client state 👉 TanStack Query manages server state That distinction changes everything. 🧠 Use Redux When: - You need a complex global UI state - Multiple components share local application state - You require predictable state transitions - Your app has complex workflows or business logic Examples: - Authentication state - Theme preferences - Multi-step forms - Shopping cart - Feature flags ⚡ Use TanStack Query When: - Fetching data from APIs - Caching server responses - Handling loading and error states - Synchronizing data automatically - Managing mutations and optimistic updates Examples: - User profiles - Product listings - Dashboard analytics - Comments and feeds 🔥 The Biggest Mistake Using Redux to manage API data manually. That often means writing: - Actions - Reducers - Loading states - Error handling - Cache logic With TanStack Query, most of that comes out of the box. --- 🎯 My Rule of Thumb - TanStack Query for anything that comes from the server - Redux for complex client-side state And in many modern apps, you’ll use both together. They’re not competitors. They’re complementary tools. Use the right tool for the right problem. #js #es6 #JavaScript #React #ReactRedux #TanStackQuery #WebDevelopment #Frontend #SoftwareEngineering

🚀 Exploring Modern Data Fetching in React with TanStack React Query In my recent work with React applications, I’ve been diving deeper into TanStack React Query and how it simplifies server-state management. 🔍Why TanStack React Query? Managing API data in React using traditional methods (useEffect + useState) can quickly become complex especially when dealing with caching, loading states, retries, and background updates. TanStack React Query solves these problems by: ✅ Automatic Caching – Reduces unnecessary API calls and improves performance ✅ Background Refetching – Keeps data fresh without manual intervention ✅ Built-in Loading & Error Handling – Cleaner and more maintainable code ✅ Pagination & Infinite Queries – Efficient handling of large datasets ✅ DevTools Support – Easy debugging and monitoring 💡 Key Advantage: It separates server state from UI state, making applications more scalable and easier to manage. 📌 Example Use Case: Instead of manually calling APIs in useEffect, we can simply use: useQuery({ queryKey: ['users'], queryFn: fetchUsers }) This approach reduces boilerplate code and improves overall developer experience. 🔥 Conclusion: If you are building modern React applications, integrating TanStack React Query can significantly enhance performance, maintainability, and user experience. #ReactJS #TanStack #ReactQuery #WebDevelopment #FrontendDevelopment #JavaScript #SoftwareDevelopment

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

🚀 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

🚀 Exploring React Query: A Game-Changer for Data Fetching! Recently, I’ve been diving into React Query, and it has completely changed how I handle server state in my React applications. Before using React Query, managing API calls meant dealing with a lot of boilerplate—loading states, error handling, caching, and refetching logic. Now, everything feels much cleaner and more efficient. ✨ What I’ve learned so far: 🔹 Simplified Data Fetching – With just a few lines of code, you can fetch, cache, and sync data effortlessly. 🔹 Automatic Caching – No need to manually store and manage API data. 🔹 Background Refetching – Keeps data fresh without interrupting the user experience. 🔹 Built-in Loading & Error States – Makes UI handling much easier. 🔹 DevTools Support – Helps visualize queries and debug effectively. 💡 One thing I really like is how it separates server state from UI state, making the application more scalable and maintainable. As someone growing in frontend development, learning tools like React Query is helping me write cleaner, more professional code. I’m excited to explore more advanced features like mutations, pagination, and query invalidation next! If you’re working with React and APIs, I highly recommend giving React Query a try 🙌 #React #ReactQuery #WebDevelopment #FrontendDevelopment #JavaScript #LearningJourney

🚀 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

🌐 Master Server-State: TanStack React Query vs. Redux 🔍 What is TanStack React Query? TanStack Query (formerly React Query) is a Server-State library. It’s designed specifically to manage asynchronous data—fetching, caching, synchronizing, and updating state that lives on a server. 📡✨ It automates the "boring" parts of development: Automatic Caching: No more manual loading spinners on every click. 🏎️ Background Refetching: Keeps your data fresh while the user stays on the page. 🔄 Error Handling: Built-in retry logic and error states. 🛠️ ⚖️ How is it different from Redux? Redux is for Client-State: It manages data that lives only in your app (like a sidebar being open, a dark mode toggle, or a multi-step form). It is highly predictable but requires lots of "boilerplate" (actions, reducers, thunks). 🧠 TanStack Query is for Server-State: It manages data that comes from an API. It replaces 50 lines of Redux boilerplate with a single, powerful hook. ⚡ 🏥 Real-Life Example: The "Library vs. Personal Notepad" 📚 Imagine you are researching a topic: Redux (Personal Notepad): You write down every single fact yourself. If a fact changes at the source, you have to manually cross it out and rewrite it. If you lose your notepad, you have nothing. 📝 TanStack Query (The Librarian): You ask the librarian for a book. They give it to you immediately if it’s on the shelf (Caching). If it’s old, they go get a new version while you keep reading (Background Update). If the book is missing, they try again automatically (Retries). 👩🏫✅ #ReactJS #TanStackQuery #Redux #WebDevelopment #FrontendArchitecture #JavaScript #StateManagement

Most Next.js devs are hitting their database twice on every page load without knowing it. One call for the metadata. One call for the page. Same query. Same data. Double the cost. In the App Router you often need the same data in two places. generateMetadata needs the post title and description. The page component needs the full post content. So you end up with two separate awaits calling the same function. Two database round trips for one page render. Most people do not even notice because it works fine. But you are paying for it on every single request. React has a built-in cache function that most devs completely overlook. Wrap your data fetching function with cache and React will memoize the result within a single request. Call it ten times, hit the database once. No extra library. No manual deduplication. Just one import from React. You define getPost once, wrapped in cache. Both generateMetadata and your page component call getPost with the same slug. The first call hits the database and stores the result. The second call returns that stored result instantly. Two awaits. One database query. Zero extra work. This is different from Next.js fetch deduplication which only works with the native fetch API. React cache works with any async function, database queries, ORM calls, third-party SDKs, anything. Code in the screenshot below 👇 #NextJS #ReactJS #FrontendDevelopment #WebDev #JavaScript

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

If you're a React + Node.js + Express.js developer, one ecosystem you should know in 2026: TanStack. It saves you from: Too many useEffects Multiple useStates for loading, error, data Manual caching headaches Repeated boilerplate in every component Before, my code looked like : useEffect + multiple useStates + copy-paste logic everywhere. Then I tried TanStack — and it changed my approach. What you get: ⚡ TanStack Query Auto caching, loading, error handling — less code, better performance ⚡ TanStack Router Type-safe routing, fewer runtime bugs ⚡ TanStack Table Built-in sorting, filtering, pagination ⚡ TanStack Start Full-stack capabilities without extra backend setup The shift: Stop thinking how to fetch data Start thinking what your app needs Link : https://lnkd.in/d5WEzUwr Still writing custom fetch logic in 2026? Try TanStack Query. One weekend is enough. #MERNStack #TanStack #ReactJS #JavaScript #WebDevelopment #NodeJS #MongoDB