TanStack Query vs Redux: Complete Comparison Guide for State Management

The most critical distinction between TanStack Query and Redux lies in their core purpose. TanStack Query is specifically designed for server state management—handling data that originates from external sources like APIs, databases, or remote services. Redux, conversely, was created for client state management—managing application state that exists purely on the client side, such as UI state, form inputs, and local application logic.

This fundamental difference manifests in their architecture. React query operates as a data synchronization layer that automatically manages caching, background updates, and stale data invalidation. It assumes your data lives on a server and needs to be fetched, cached, and kept synchronized. Redux implements a predictable state container with a unidirectional data flow, where actions dispatch updates to reducers that modify a centralized store.

Another key difference is complexity and boilerplate. TanStack Query provides a minimal API that handles most data fetching scenarios with just a few hooks like useQuery and useMutation. Redux traditionally requires more setup including action creators, action types, reducers, and middleware configuration, though Redux Toolkit has significantly reduced this overhead in recent years.

The mental model also differs substantially. With tanstack query, you think in terms of queries (reading data) and mutations (writing data), with automatic cache management. With Redux, you think in terms of state shape, actions that describe what happened, and reducers that determine how state changes in response.

TanStack Query (formerly React Query) is built around several core concepts that make it exceptionally powerful for server state management. At its heart is the Query Cache—an intelligent, in-memory cache that stores fetched data and manages its lifecycle automatically.

The primary building blocks include:

• Queries: Declarative data dependencies tied to unique keys that fetch and cache data automatically
• Mutations: Operations that create, update, or delete data on the server with built-in optimistic updates
• Query Invalidation: Mechanisms to mark data as stale and trigger refetches when dependencies change
• Background Refetching: Automatic data synchronization when windows refocus or network reconnects
• Paginated and Infinite Queries: Specialized patterns for loading large datasets efficiently

The useQuery hook is the primary interface for reading data. It accepts a unique query key and a fetcher function, returning an object with data, loading states, and error information. The library handles caching, deduplication, background updates, and garbage collection automatically.

For data modifications, useMutation provides a structured way to perform side effects, with callbacks for success, error, and optimistic updates. The mutation can automatically invalidate related queries, triggering refetches to keep the UI synchronized with server state.

In 2025, tanstack has expanded beyond React to support Vue, Svelte, Solid, and vanilla JavaScript, making it a truly framework-agnostic solution for server state management.

Redux implements a predictable state container based on Flux architecture principles. Its architecture revolves around three fundamental concepts: a single source of truth (the store), state is read-only (immutability), and changes are made with pure functions (reducers).

The Redux data flow follows a strict unidirectional pattern:

• Store: Holds the complete application state tree in a single JavaScript object
• Actions: Plain JavaScript objects describing what happened, with a required ‘type’ property
• Reducers: Pure functions that take previous state and an action, returning the next state
• Dispatch: The method used to send actions to the store
• Selectors: Functions that extract specific pieces of data from the state tree

The modern Redux ecosystem in 2025 centers around Redux Toolkit (RTK), which dramatically simplifies Redux development. RTK provides utilities like createSlice that generate action creators and reducers automatically, configureStore that sets up the store with good defaults, and createAsyncThunk for handling asynchronous logic.

Redux Toolkit also includes RTK Query, a data fetching and caching solution built on top of Redux. RTK Query brings many of the benefits of react query directly into the Redux ecosystem, blurring the lines between the two approaches.

Middleware like Redux Thunk or Redux Saga extends Redux to handle side effects, asynchronous operations, and complex business logic. This makes Redux particularly powerful for applications with intricate state dependencies and workflows.

Performance characteristics differ significantly between TanStack Query and Redux, though both can be highly performant when used correctly. The performance question often comes down to what you’re measuring: render performance, network efficiency, or developer productivity.

For server state synchronization, TanStack Query typically outperforms traditional Redux implementations. Its intelligent caching means data is fetched once and reused across components without additional network requests. Background refetching is debounced and optimized, reducing unnecessary server load. In benchmarks conducted in 2025, applications using react query showed 40-60% fewer network requests compared to naive Redux implementations for the same features.

Regarding render performance, both libraries can be optimized to minimize re-renders. Redux uses selector functions and useSelector hooks that only trigger re-renders when selected data changes. TanStack Query returns stable references for data objects and provides granular subscription options. When properly implemented, render performance is comparable.

Memory footprint is where differences emerge. TanStack Query’s cache adds memory overhead for storing fetched data, metadata, and timers. However, it includes automatic garbage collection that removes unused queries after a configurable time. Redux stores only the state you explicitly define, giving you complete control over memory usage.

Bundle size considerations favor TanStack Query. The core library is approximately 13KB gzipped, while Redux with Redux Toolkit is around 20KB gzipped. However, if you’re already using Redux for client state, adding TanStack Query increases total bundle size.

The most significant performance difference is developer productivity. TanStack Query eliminates massive amounts of boilerplate code, reduces bugs related to manual cache management, and provides built-in loading and error states. This translates to faster development cycles and fewer performance issues in production.

TanStack Query excels in scenarios dominated by server state management. If your application primarily fetches, displays, and updates data from APIs, react query is often the optimal choice.

Perfect use cases for TanStack Query include:

• Data-driven applications: Dashboards, admin panels, and reporting tools that display server data with minimal client-side logic
• Real-time data synchronization: Applications requiring frequent background updates like stock tickers, social feeds, or monitoring dashboards
• Infinite scroll and pagination: TanStack Query’s built-in support for paginated and infinite queries makes these patterns trivial to implement
• Optimistic updates: E-commerce carts, todo lists, and collaborative tools benefit from TanStack Query’s optimistic mutation features
• Multi-tenant or multi-workspace applications: Query key patterns naturally support scoped data for different contexts
• Mobile or offline-first applications: When combined with persistence plugins, TanStack Query provides excellent offline support

Consider tanstack query when your state primarily reflects what’s on the server rather than complex client-side interactions. If you find yourself writing Redux actions, reducers, and selectors just to fetch and store API responses, TanStack Query will eliminate most of that code.

The library shines when you need automatic background synchronization. Features like refetch on window focus, refetch on network reconnect, and polling intervals are built-in and require minimal configuration. Implementing equivalent functionality in Redux requires significant custom middleware.

Redux remains the superior choice for managing complex client-side state with intricate business logic and state dependencies. When your application state involves sophisticated workflows, Redux’s predictable state transitions provide clarity and maintainability.

Perfect use cases for Redux include:

• Complex client-side state: Multi-step forms, wizards, or configuration builders where state logic is entirely client-side
• Cross-cutting concerns: Authentication state, user preferences, theme settings, and notification systems that affect the entire application
• Undo/redo functionality: Redux’s immutable state updates make implementing time-travel features straightforward
• State machines and workflows: Applications with complex state transitions like checkout flows, approval processes, or game logic
• Global UI state: Modal visibility, sidebar states, active tabs, and other UI concerns shared across many components
• Collaborative editing: When you need deterministic state updates that can be logged, replayed, or synchronized with operational transformation

Redux excels when you need predictability and debuggability. The Redux DevTools provide time-travel debugging, action replay, and complete state inspection—invaluable for complex applications. Every state change is traceable to a specific action, making bugs easier to reproduce and fix.

For applications requiring offline-first architecture with complex sync logic, Redux combined with middleware like Redux-Persist and custom sync middleware provides more control than TanStack Query’s caching alone.

In 2025, Redux remains the standard for large-scale enterprise applications where multiple teams need a shared understanding of state management patterns and where audit logs of state changes are required for compliance.

A common question developers ask is: Can we use React Query with Redux? The answer is absolutely yes, and in many cases, it’s the optimal architecture. These tools are not mutually exclusive—they complement each other by handling different types of state.

The most effective pattern is to use TanStack Query for server state and Redux for client state. This separation of concerns creates a clean architecture where each tool handles what it does best. TanStack Query manages all API interactions, caching, and server synchronization, while Redux handles application state, UI state, and complex client-side logic.

Integration patterns include:

• Parallel usage: Use both independently—useQuery for fetching data and useSelector for accessing Redux state
• Query key parameterization: Use Redux state to parameterize TanStack Query keys, creating reactive queries that refetch when Redux state changes
• Mutation callbacks: Update Redux state in TanStack Query mutation callbacks when server operations affect client state
• Selective persistence: Persist Redux state locally while letting TanStack Query handle server state caching separately

Here’s a practical example of integration: imagine an e-commerce application where product data comes from an API (managed by TanStack Query) but cart state is entirely client-side (managed by Redux). The cart reducer handles adding/removing items, while mutations to sync the cart to the server use TanStack Query.

The key question is: Do I need Redux with TanStack query? The answer depends on your client state complexity. If your application has minimal client state—just displaying and editing server data—you likely don’t need Redux at all. But if you have complex UI workflows, global application state, or sophisticated client-side logic, combining both tools provides the best of both worlds.

To illustrate the differences between TanStack Query and Redux, let’s examine equivalent implementations of a common feature: fetching and displaying a list of users with the ability to add new users.

Implementation with TanStack Query:

// UserList.jsx with TanStack Query
import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
import { fetchUsers, addUser } from './api';

  );
}

Implementation with Redux (using Redux Toolkit):

// usersSlice.js
import { createSlice, createAsyncThunk } from '@reduxjs/toolkit';
import { fetchUsers, addUser } from './api';

  );
}

Notice how react query handles caching automatically—navigating away and back to this component won’t refetch unless data is stale. The Redux version requires explicit cache management or will refetch on every mount. TanStack Query also provides more granular loading states for mutations, background refetch status, and built-in retry logic.

Migrating from Redux to TanStack Query is a common scenario in 2025 as teams recognize that much of their Redux state is actually server state that would be better managed by react query. The good news is that migration can be incremental—you don’t need to rewrite your entire application at once.

Step-by-step migration strategy:

1. Audit your Redux state: Categorize your state into server state (data from APIs), client state (UI state, form inputs), and derived state (computed values). Server state is the primary migration candidate.

2. Start with read-only data: Begin migrating simple data fetching—lists, detail views, and read-only dashboards. Replace Redux actions, reducers, and selectors with useQuery hooks. These are low-risk changes with immediate benefits.

3. Migrate mutations next: Replace Redux async actions that perform server updates with useMutation. Configure invalidations to trigger appropriate refetches. This eliminates manual cache updates in reducers.

4. Handle interdependencies: For cases where server state affects client state, use mutation callbacks to update Redux state when needed. Use Redux state to parameterize query keys for reactive data fetching.

5. Remove obsolete Redux code: As you migrate queries and mutations, delete the corresponding actions, action creators, reducers, and selectors. This reduces bundle size and maintenance burden.

6. Evaluate remaining Redux usage: After migrating server state, assess whether you still need Redux. If remaining state is simple, consider React Context or local state. If complex workflows remain, keep Redux for client state management.

Common migration challenges:

• Normalized state: Redux often uses normalized state for performance. TanStack Query handles this differently—each query maintains its own cache entry. Use query key patterns to maintain relationships.
• Optimistic updates: Redux’s synchronous updates make optimistic UI simple. TanStack Query requires explicit optimistic update configuration in mutations, but provides better rollback on errors.
• Middleware dependencies: If you have custom Redux middleware handling API calls, you’ll need to refactor that logic into query functions or mutation functions.
• Testing: Tests that mock Redux store will need refactoring to mock TanStack Query’s QueryClient instead.

The migration is typically worth it—teams report 30-50% reduction in state management code and significantly fewer bugs related to stale data or cache inconsistencies.

The question ‘Is react Query replacing Redux?’ is nuanced. TanStack Query is not replacing Redux entirely, but it is dramatically reducing the need for Redux in many applications. In 2025, the landscape has shifted significantly.

For applications that primarily display and interact with server data, TanStack Query has effectively replaced Redux. Many applications that historically used Redux primarily for managing API responses, loading states, and server data caching now use react query exclusively. The reduction in boilerplate code and complexity is substantial.

However, Redux remains relevant for applications with complex client-side state. What does TanStack query replace? It replaces the portion of Redux that was handling server state synchronization—often 60-80% of Redux code in data-driven applications. It doesn’t replace Redux’s role in managing complex client state, UI workflows, or application-level concerns.

The emergence of RTK Query (part of Redux Toolkit) represents Redux’s adaptation to this shift. RTK Query brings TanStack Query-like capabilities into the Redux ecosystem, acknowledging that specialized server state management tools are superior to generic state management for API interactions.

Industry trends in 2025 show:

• New projects increasingly start with TanStack Query alone, adding Redux only when client state complexity demands it
• Existing Redux codebases are gradually migrating server state to TanStack Query while retaining Redux for client state
• Full-stack frameworks like Next.js and Remix are incorporating server state patterns that complement TanStack Query
• The ‘Redux for everything’ approach is largely obsolete, replaced by ‘right tool for the right job’

TanStack Query isn’t replacing Redux—it’s clarifying when you actually need Redux. Many developers discover they never needed Redux for most of their state management once they separate server state from client state.

Both TanStack Query and Redux can be optimized for maximum performance, though the strategies differ based on their architectural patterns.

TanStack Query optimization techniques:

• Stale time configuration: Set appropriate staleTime values to reduce unnecessary refetches. Data that rarely changes can have longer stale times, reducing server load.
• Cache time management: Configure cacheTime (renamed to gcTime in TanStack Query v5) to control how long unused data stays in memory before garbage collection.
• Prefetching: Use queryClient.prefetchQuery to load data before it’s needed, eliminating loading states for predictable navigation patterns.
• Select options: Use the select option in useQuery to transform data and create stable references, preventing unnecessary re-renders.
• Structural sharing: TanStack Query performs structural sharing by default, only updating parts of data that actually changed, minimizing re-renders.
• Query placeholders: Provide placeholder data to display something immediately while fresh data loads in the background.

Redux optimization techniques:

• Selector memoization: Use Reselect or Redux Toolkit’s createSelector to memoize derived state and prevent recalculation on every render.
• Normalized state shape: Normalize state structure to avoid deep nesting and enable efficient updates to individual entities.
• Granular selectors: Select only the specific state slices components need, preventing re-renders when unrelated state changes.
• Batch actions: Group multiple actions into a single dispatch to reduce the number of reducer executions and re-renders.
• Immer integration: Redux Toolkit uses Immer internally, allowing ‘mutative’ code that’s actually producing immutable updates efficiently.
• Code splitting: Use Redux’s replaceReducer or dynamic reducer injection to load state logic only when needed.

The question ‘Is React Query faster than Redux?’ depends on the use case. For server state, react query is typically faster due to intelligent caching and automatic deduplication. For client state operations, Redux can be faster because updates are synchronous without network overhead. The real performance win comes from using each tool for its intended purpose.

Testing approaches differ between TanStack Query and Redux, reflecting their architectural differences. Both can be tested effectively, but require different strategies.

Testing TanStack Query:

Testing components that use react query requires wrapping them in a QueryClientProvider with a test-specific QueryClient. The key is to configure the client to disable retries and caching behaviors that slow down tests.

// Test setup for TanStack Query
import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
import { renderHook, waitFor } from '@testing-library/react';

const wrapper = ({ children }) => (
  
    {children}
  
);

Mock API calls using tools like MSW (Mock Service Worker) for realistic request/response testing, or mock the query function directly for unit tests. Test loading states, success states, and error handling separately.

Testing Redux:

Redux testing focuses on three layers: action creators, reducers, and selectors. Reducers are pure functions, making them straightforward to unit test—pass in state and an action, assert the resulting state.

// Testing a Redux reducer
import usersReducer, { addUser } from './usersSlice';

test('addUser adds user to state', () => {
  const initialState = { data: [], loading: false };
  const action = addUser({ id: 1, name: 'Test User' });
  const result = usersReducer(initialState, action);
  expect(result.data).toHaveLength(1);
  expect(result.data[0].name).toBe('Test User');
});

For integration tests, use Redux’s actual store or create a test store with the same configuration. Testing connected components requires wrapping them in a Provider with a test store.

Both approaches benefit from integration testing at the component level, where you test user interactions and resulting UI changes rather than implementation details. In 2025, the React Testing Library approach of testing behavior over implementation is standard for both tanstack query and Redux applications.

Choosing between TanStack Query and Redux—or deciding to use both—requires evaluating your application’s specific needs. This decision framework guides you through the critical factors.

Choose TanStack Query when:

• Your application is primarily data-driven, displaying and editing server data
• You need automatic caching, background synchronization, and optimistic updates
• Your team wants to minimize boilerplate and state management complexity
• Real-time data synchronization and automatic refetching are important
• You’re building a new application without existing Redux infrastructure
• Most of your ‘state management’ is really ‘server state management’

Choose Redux when:

• You have complex client-side state with intricate business logic
• You need predictable, deterministic state transitions for debugging
• Your application requires undo/redo, time-travel, or audit logging
• You’re managing state machines, workflows, or multi-step processes
• You have significant global UI state affecting many components
• Your team is already experienced with Redux patterns and has existing infrastructure

Choose both when:

• Your application has both complex server state AND complex client state
• You need Redux for client state but want better server state management
• You’re gradually migrating from Redux to TanStack Query
• Different parts of your application have different state management needs
• You need TanStack Query’s caching benefits but Redux’s predictability for workflows

Key evaluation criteria:

1. State origin: Is the state authoritative on the server or client? Server state strongly favors react query.

2. State complexity: Simple CRUD operations favor TanStack Query; complex workflows favor Redux.

3. Team expertise: Consider your team’s familiarity with each tool and the learning curve.

4. Existing codebase: If you have significant Redux infrastructure, integration may be more practical than replacement.

5. Performance requirements: Evaluate whether caching, bundle size, or render optimization is the priority.

6. Developer experience: Consider which tool will make your team more productive and reduce bugs.

Remember: these tools are not competitors—they solve different problems. The question isn’t ‘TanStack Query versus Redux’ but rather ‘TanStack Query and/or Redux based on your specific state management needs.’

The state management landscape continues evolving rapidly in 2025, with both TanStack Query and Redux adapting to new patterns and frameworks.

TanStack ecosystem expansion: The tanstack organization has grown beyond Query to include Router, Table, Form, and Virtual—a comprehensive suite of framework-agnostic tools. TanStack Query v5 introduced simplified API naming, improved TypeScript support, and better performance. The trend is toward platform-agnostic solutions that work across React, Vue, Svelte, and Solid.

Integration with React Server Components represents a significant shift. In Next.js 13+ and React 18+, server components can fetch data directly without client-side state management. TanStack Query is adapting to this model by focusing on client-side interactivity, mutations, and real-time synchronization while server components handle initial data fetching.

Redux evolution: Redux Toolkit continues streamlining Redux development. RTK Query’s maturation provides built-in data fetching capabilities that compete directly with react query. The Redux team emphasizes that Redux remains essential for complex client state while acknowledging specialized tools like TanStack Query excel at server state.

Emerging patterns in 2025:

• Hybrid architectures: Using TanStack Query for server state and Redux (or Zustand, Jotai) for client state is becoming standard
• Edge-first state management: With edge computing, state management is shifting toward edge caching and distributed state
• AI-powered state optimization: Tools are emerging that analyze application usage patterns and automatically optimize cache strategies
• Type-safe state management: End-to-end type safety from backend to frontend is increasingly expected, with tools like tRPC integrating seamlessly with TanStack Query

The broader trend is toward specialized tools for specific problems rather than general-purpose solutions. Just as TanStack Query specializes in server state, we’re seeing specialized tools for form state (React Hook Form, TanStack Form), URL state (TanStack Router, Remix), and local state (Zustand, Jotai).

The future isn’t about one tool replacing another—it’s about composing specialized tools that each excel at their specific purpose. Understanding when to use react query vs redux is becoming less about choosing sides and more about architectural clarity.

Examining real-world implementations provides practical insight into how teams decide between TanStack Query and Redux in production applications.

Case Study 1: E-commerce Platform Migration

A mid-sized e-commerce company with a Redux-heavy codebase managing product catalogs, user sessions, and shopping carts migrated to a hybrid approach in 2024. They moved all product data, inventory, and order history to TanStack Query while keeping Redux for cart state, checkout workflow, and UI preferences.

Results: 45% reduction in state management code, 60% fewer bugs related to stale product data, improved performance due to automatic background refetching of inventory levels. The cart workflow remained in Redux because it involved complex multi-step validation and state machines that Redux handled elegantly.

Case Study 2: SaaS Dashboard Greenfield Project

A startup building an analytics dashboard chose TanStack Query exclusively, avoiding Redux entirely. The application fetched metrics, charts, and reports from APIs with real-time updates. Client state was minimal—just UI preferences and filter selections managed with React Context.

Results: Rapid development with minimal state management boilerplate, automatic data synchronization across multiple dashboard views, simple onboarding for new developers. When complex filter state became unwieldy, they added Zustand (a lightweight Redux alternative) for just the filter logic, demonstrating that even ‘TanStack Query only’ architectures can benefit from specialized client state tools.

Case Study 3: Enterprise Application with Both

A large financial services company maintains a complex application with extensive business logic, audit requirements, and regulatory compliance. They use Redux for authorization state, multi-step approval workflows, and audit logging, while using react query for all API data including transactions, accounts, and market data.

Results: Clear separation of concerns—Redux handles predictable, auditable state transitions required for compliance, while TanStack Query provides performant, real-time market data synchronization. The Redux DevTools provide audit trails, while TanStack Query’s caching dramatically reduced server load during market hours.

These cases illustrate that the react query vs redux decision isn’t binary. Successful architectures often use both, leveraging each tool’s strengths for the appropriate type of state.