React Query vs SWR vs TanStack: Ultimate 2025 Guide

The landscape of React data fetching libraries has evolved dramatically, with developers now having powerful options that go far beyond basic fetch() calls. As React applications become more complex—especially in PropTech where real-time property data, user interactions, and complex state management are crucial—choosing the right data fetching solution can make or break your application's performance and developer experience.

The Evolution of React Data Fetching Libraries

Data fetching in React has transformed from simple component-level API calls to sophisticated state management solutions. The emergence of libraries like React Query, SWR, and TanStack Query has revolutionized how we handle server state, caching, and synchronization.

Why Traditional Approaches Fall Short

Traditional data fetching approaches using useEffect and useState create several challenges:

Manual cache management leading to inconsistent data
No automatic background refetching or synchronization
Complex loading and error state management
Duplicated requests across components
Poor offline experience and stale data handling

In PropTech applications, where property listings, pricing data, and user preferences need constant synchronization, these limitations become critical bottlenecks.

The Modern Data Fetching Paradigm

Modern libraries treat server state as a first-class citizen, distinct from client state. They provide:

Intelligent caching strategies
Automatic background synchronization
Optimistic updates and rollback mechanisms
Built-in loading, error, and success states
Request deduplication and batching

Understanding the Core Players

React Query (Legacy) vs TanStack Query

React Query was rebranded to TanStack Query in 2022, expanding beyond React to support Vue, Svelte, and other frameworks. While "React Query" often refers to TanStack Query's React adapter, understanding this distinction is crucial for 2025.

// TanStack Query v5(latest)
import { useQuery } from &#039;@tanstack/react-query&#039;

class="kw">const PropertyQuery = () => {
  class="kw">const { data, isLoading, error } = useQuery({
    queryKey: [&#039;properties&#039;, filters],
    queryFn: () => fetchProperties(filters),
    staleTime: 5  60  1000, // 5 minutes
  })

  class="kw">return (
    <div>
      {isLoading && <PropertySkeleton />}
      {error && <ErrorBoundary error={error} />}
      {data && <PropertyList properties={data} />}
    </div>
  )

}

SWR: Stale-While-Revalidate Philosophy

SWR, developed by Vercel, implements the stale-while-revalidate HTTP caching strategy. It's lightweight, focused, and integrates seamlessly with Next.js applications.

import useSWR from &#039;swr&#039;

class="kw">const PropertyDetails = ({ propertyId }: { propertyId: string }) => {
  class="kw">const { data, error, mutate } = useSWR(
    /api/properties/${propertyId},
    fetcher,
    {
      revalidateOnFocus: true,
      revalidateOnReconnect: true,
    }
  )

  class="kw">const updateProperty = class="kw">async (updates: PropertyUpdates) => {
    // Optimistic update
    mutate({ ...data, ...updates }, false)
    class="kw">await updatePropertyAPI(propertyId, updates)
    mutate() // Revalidate
  }

  class="kw">return <PropertyCard data={data} onUpdate={updateProperty} />

}

Feature Comparison Matrix

|---------|----------------|-----|-----------------|

| Bundle Size | ~39kb | ~4.2kb | ~36kb |

| Request Deduplication | Yes | Yes | Yes |

Implementation Deep Dive

Setting Up Your Data Layer

When building PropTech applications, establishing a robust data layer is essential. Here's how each library approaches setup:

#### TanStack Query Setup

// queryClient.ts
import { QueryClient } from &#039;@tanstack/react-query&#039;

export class="kw">const queryClient = new QueryClient({
  defaultOptions: {
    queries: {
      staleTime: 1000  60  5, // 5 minutes
      gcTime: 1000  60  30, // 30 minutes(formerly cacheTime)
      retry: (failureCount, error) => {
        class="kw">if (error.status === 404) class="kw">return false
        class="kw">return failureCount < 3
      },
    },
  },
})

// App.tsx
import { QueryClientProvider } from &#039;@tanstack/react-query&#039;
import { ReactQueryDevtools } from &#039;@tanstack/react-query-devtools&#039;

class="kw">function App() {
  class="kw">return (
    <QueryClientProvider client={queryClient}>
      <PropertyApp />
      <ReactQueryDevtools initialIsOpen={false} />
    </QueryClientProvider>
  )

}

#### SWR Configuration

// _app.tsx(Next.js)
import { SWRConfig } from &#039;swr&#039;
import axios from &#039;axios&#039;

class="kw">const fetcher = (url: string) => axios.get(url).then(res => res.data)

class="kw">function MyApp({ Component, pageProps }) {
  class="kw">return (
    <SWRConfig
      value={{
        fetcher,
        revalidateOnFocus: false,
        errorRetryCount: 3,
        errorRetryInterval: 5000,
        dedupingInterval: 2000,
      }}
    >
      <Component {...pageProps} />
    </SWRConfig>
  )

}

Advanced Patterns and Real-World Examples

#### Infinite Queries for Property Listings

Propertytech applications often require infinite scrolling for large datasets:

// TanStack Query infinite query
import { useInfiniteQuery } from &#039;@tanstack/react-query&#039;

class="kw">const useInfiniteProperties = (filters: PropertyFilters) => {
  class="kw">return useInfiniteQuery({
    queryKey: [&#039;properties&#039;, &#039;infinite&#039;, filters],
    queryFn: ({ pageParam = 0 }) => 
      fetchProperties({ ...filters, page: pageParam }),
    getNextPageParam: (lastPage, pages) => 
      lastPage.hasNext ? pages.length : undefined,
    initialPageParam: 0,
  })
}

class="kw">const PropertyListContainer = () => {
  class="kw">const { 
    data, 
    fetchNextPage, 
    hasNextPage, 
    isFetchingNextPage 
  } = useInfiniteProperties(filters)

  class="kw">return (
    <InfiniteScroll
      dataLength={data?.pages.flatMap(p => p.properties).length ?? 0}
      next={fetchNextPage}
      hasMore={hasNextPage}
      loader={<PropertySkeleton />}
    >
      {data?.pages.map(page => 
        page.properties.map(property => 
          <PropertyCard key={property.id} property={property} />
        )
      )}
    </InfiniteScroll>
  )

}

#### SWR Infinite Loading

import useSWRInfinite from &#039;swr/infinite&#039;

class="kw">const useInfinitePropertiesSWR = (filters: PropertyFilters) => {
  class="kw">const getKey = (pageIndex: number, previousPageData: any) => {
    class="kw">if (previousPageData && !previousPageData.hasNext) class="kw">return null
    class="kw">return /api/properties?page=${pageIndex}&${new URLSearchParams(filters)}
  }

  class="kw">return useSWRInfinite(getKey, fetcher)

}

Handling Complex State Synchronization

In PropTech applications, you often need to synchronize related data. Here's how each library handles dependent queries:

// TanStack Query dependent queries
class="kw">const usePropertyWithDetails = (propertyId: string) => {
  class="kw">const propertyQuery = useQuery({
    queryKey: [&#039;property&#039;, propertyId],
    queryFn: () => fetchProperty(propertyId),
  })

  class="kw">const neighborhoodQuery = useQuery({
    queryKey: [&#039;neighborhood&#039;, propertyQuery.data?.neighborhoodId],
    queryFn: () => fetchNeighborhood(propertyQuery.data.neighborhoodId),
    enabled: !!propertyQuery.data?.neighborhoodId,
  })

  class="kw">const marketDataQuery = useQuery({
    queryKey: [&#039;marketData&#039;, propertyQuery.data?.zipCode],
    queryFn: () => fetchMarketData(propertyQuery.data.zipCode),
    enabled: !!propertyQuery.data?.zipCode,
  })

  class="kw">return {
    property: propertyQuery.data,
    neighborhood: neighborhoodQuery.data,
    marketData: marketDataQuery.data,
    isLoading: propertyQuery.isLoading,
    error: propertyQuery.error || neighborhoodQuery.error || marketDataQuery.error,
  }

}

💡

Pro Tip

When working with dependent queries, always use the enabled option to prevent unnecessary API calls and improve performance.

Best Practices and Performance Optimization

Choosing the Right Library for Your Use Case

The decision between these libraries depends on your specific requirements:

#### Choose TanStack Query When:

Building complex applications with sophisticated data requirements
Need advanced features like infinite queries, parallel queries, and mutations
Want comprehensive DevTools for debugging
Planning to expand beyond React (Vue, Svelte support)
Building PropTech platforms with complex property data relationships

#### Choose SWR When:

Building with Next.js and want seamless integration
Prefer a lightweight solution with minimal bundle impact
Need simple, effective caching with good defaults
Want to implement custom fetching logic easily
Building content-heavy applications where stale-while-revalidate shines

Performance Optimization Strategies

#### Query Key Management

// Good: Consistent, predictable query keys
class="kw">const propertyKeys = {
  all: [&#039;properties&#039;] as class="kw">const,
  lists: () => [...propertyKeys.all, &#039;list&#039;] as class="kw">const,
  list: (filters: PropertyFilters) => [...propertyKeys.lists(), { filters }] as class="kw">const,
  details: () => [...propertyKeys.all, &#039;detail&#039;] as class="kw">const,
  detail: (id: string) => [...propertyKeys.details(), id] as class="kw">const,
}

// Usage
class="kw">const { data } = useQuery({
  queryKey: propertyKeys.detail(propertyId),
  queryFn: () => fetchProperty(propertyId),

})

#### Smart Caching Strategies

// Configure different stale times based on data volatility
class="kw">const usePropertyData = (propertyId: string) => {
  // Property details change infrequently
  class="kw">const propertyQuery = useQuery({
    queryKey: [&#039;property&#039;, propertyId],
    queryFn: () => fetchProperty(propertyId),
    staleTime: 10  60  1000, // 10 minutes
  })

  // Market data changes frequently
  class="kw">const marketQuery = useQuery({
    queryKey: [&#039;market&#039;, propertyQuery.data?.zipCode],
    queryFn: () => fetchMarketData(propertyQuery.data.zipCode),
    staleTime: 30 * 1000, // 30 seconds
    enabled: !!propertyQuery.data?.zipCode,
  })

  class="kw">return { property: propertyQuery.data, market: marketQuery.data }

}

Error Handling and User Experience

// Comprehensive error handling
class="kw">const useResilientPropertyQuery = (propertyId: string) => {
  class="kw">return useQuery({
    queryKey: [&#039;property&#039;, propertyId],
    queryFn: class="kw">async () => {
      try {
        class="kw">return class="kw">await fetchProperty(propertyId)
      } catch (error) {
        class="kw">if (error.status === 404) {
          throw new Error(&#039;Property not found&#039;)
        }
        throw error
      }
    },
    retry: (failureCount, error) => {
      class="kw">if (error.message === &#039;Property not found&#039;) class="kw">return false
      class="kw">return failureCount < 3
    },
    retryDelay: attemptIndex => Math.min(1000  2 * attemptIndex, 30000),
  })

}

⚠️

Warning

Always implement proper error boundaries and fallback UI components to handle network failures gracefully, especially in PropTech applications where users expect real-time data.

Testing Strategies

// Mock queries class="kw">for testing
import { QueryClient } from &#039;@tanstack/react-query&#039;
import { renderWithQuery } from &#039;../test-utils&#039;

describe(&#039;PropertyDetails&#039;, () => {
  it(&#039;renders property data correctly&#039;, class="kw">async () => {
    class="kw">const queryClient = new QueryClient({
      defaultOptions: {
        queries: { retry: false },
        mutations: { retry: false },
      },
    })

    // Prefill cache
    queryClient.setQueryData([&#039;property&#039;, &#039;123&#039;], mockPropertyData)

    class="kw">const { findByText } = renderWithQuery(
      <PropertyDetails propertyId="123" />,
      queryClient
    )

    expect(class="kw">await findByText(&#039;Modern Downtown Condo&#039;)).toBeInTheDocument()
  })

})

The 2025 Verdict: Making Your Decision

As we look at the data fetching landscape in 2025, each library has carved out its niche. At PropTechUSA.ai, where we handle complex property data workflows, real-time market updates, and sophisticated user interactions, the choice often comes down to project scope and team expertise.

TanStack Query: The Comprehensive Solution

TanStack Query has emerged as the most feature-complete solution. Its v5 release brings improved TypeScript support, better performance, and framework-agnostic capabilities. The learning curve is steeper, but the payoff is substantial for complex applications.

Best for: Large PropTech platforms, applications with complex data relationships, teams that need advanced debugging and optimization tools.

SWR: The Elegant Minimalist

SWR continues to excel in its simplicity and effectiveness. Its small bundle size and excellent Next.js integration make it perfect for projects where simplicity and performance are paramount.

Best for: Content-heavy sites, Next.js applications, projects prioritizing bundle size, teams preferring minimal configuration.

Migration Considerations

If you're currently using React Query v3, migrating to TanStack Query v5 provides significant benefits but requires careful planning. SWR offers easier migration paths and can be introduced incrementally.

The future of React data fetching is bright, with all three libraries continuing active development. Your choice should align with your team's expertise, project requirements, and long-term maintenance goals. Whether you're building the next generation of property management tools or creating immersive real estate experiences, any of these libraries will serve you well when implemented thoughtfully.

Ready to implement robust data fetching in your PropTech application? Start with a proof of concept using your chosen library and gradually migrate your most critical data flows. The investment in proper data management will pay dividends in application performance, developer experience, and user satisfaction.