jotai vs. recoil
Side-by-side comparison · 9 metrics · 14 criteria
- Weekly Downloads
- 6.4M
- Stars
- 21.3K
- Gzip Size
- 6.6 kB
- License
- MIT
- Last Updated
- 7mo ago
- Open Issues
- 1
- Forks
- 724
- Unpacked Size
- 112.8 kB
- Dependencies
- 2
- Weekly Downloads
- 455.0K
- Stars
- 19.4K
- Gzip Size
- 29.5 kB
- License
- MIT
- Last Updated
- 2y ago
- Open Issues
- 320
- Forks
- 1.2K
- Unpacked Size
- 2.2 MB
- Dependencies
- 3
jotai vs recoil downloads · last 12 months
Criteria · jotai vs recoil
- API Surface
- jotai ✓Minimal and focused API, closely mirroring React's hook patterns.recoilMore extensive API with distinct concepts for atoms, selectors, and snapshots.
- Extensibility
- jotai ✓Highly extensible through community add-ons and custom hooks.recoilOffers a robust core with potential for custom integration.
- Learning Curve
- jotai ✓Gentle learning curve for developers familiar with React hooks.recoilSlightly steeper initial learning curve due to distinct concepts.
- Project Origin
- jotaiCommunity-driven project with a strong focus on core primitives.recoil ✓Developed and backed by Meta (Facebook), indicating significant resources.
- Core Philosophy
- jotai ✓Primitive and flexible building blocks for state management, emphasizing composition.recoilComprehensive and integrated state management library for complex React applications.
- State Debugging
- jotaiDebuggable through React DevTools and custom hooks for inspection.recoil ✓Provides tools and snapshots for debugging complex state scenarios.
- Reactivity Model
- jotaiAutomatic subscription to atomic state changes for efficient re-renders.recoilSelector graph efficiently recomputes derived state based on atom changes.
- State Granularity
- jotai ✓Highly granular atomic state management, akin to fine-grained React hooks.recoilUnified atom and selector model for managing state and derived data.
- TypeScript Support
- jotaiExcellent TypeScript support, leveraging type inference and generics.recoilRobust TypeScript support integrated into its core API design.
- Dependency Footprint
- jotai ✓Virtually zero dependencies, contributing to its small size.recoilHas dependencies, contributing to its larger footprint.
- Developer Experience
- jotai ✓Intuitive for React developers, emphasizing composability and minimal boilerplate.recoilStructured approach that can lead to more predictable state flow in large apps.
- Bundle Size Efficiency
- jotai ✓Extremely small bundle size, ideal for performance-sensitive applications.recoilLarger bundle size compared to Jotai, suitable for applications where this is less critical.
- Derived State Handling
- jotaiDerived state managed through atom composition and utilities.recoil ✓Integrated selector system with built-in support for asynchronous operations and caching.
- Asynchronous Operations
- jotaiSupported through composition and utilities, potentially requiring more manual setup.recoil ✓Natively supported and optimized within the selector API.
| Criteria | jotai | recoil |
|---|---|---|
| API Surface | ✓ Minimal and focused API, closely mirroring React's hook patterns. | More extensive API with distinct concepts for atoms, selectors, and snapshots. |
| Extensibility | ✓ Highly extensible through community add-ons and custom hooks. | Offers a robust core with potential for custom integration. |
| Learning Curve | ✓ Gentle learning curve for developers familiar with React hooks. | Slightly steeper initial learning curve due to distinct concepts. |
| Project Origin | Community-driven project with a strong focus on core primitives. | ✓ Developed and backed by Meta (Facebook), indicating significant resources. |
| Core Philosophy | ✓ Primitive and flexible building blocks for state management, emphasizing composition. | Comprehensive and integrated state management library for complex React applications. |
| State Debugging | Debuggable through React DevTools and custom hooks for inspection. | ✓ Provides tools and snapshots for debugging complex state scenarios. |
| Reactivity Model | Automatic subscription to atomic state changes for efficient re-renders. | Selector graph efficiently recomputes derived state based on atom changes. |
| State Granularity | ✓ Highly granular atomic state management, akin to fine-grained React hooks. | Unified atom and selector model for managing state and derived data. |
| TypeScript Support | Excellent TypeScript support, leveraging type inference and generics. | Robust TypeScript support integrated into its core API design. |
| Dependency Footprint | ✓ Virtually zero dependencies, contributing to its small size. | Has dependencies, contributing to its larger footprint. |
| Developer Experience | ✓ Intuitive for React developers, emphasizing composability and minimal boilerplate. | Structured approach that can lead to more predictable state flow in large apps. |
| Bundle Size Efficiency | ✓ Extremely small bundle size, ideal for performance-sensitive applications. | Larger bundle size compared to Jotai, suitable for applications where this is less critical. |
| Derived State Handling | Derived state managed through atom composition and utilities. | ✓ Integrated selector system with built-in support for asynchronous operations and caching. |
| Asynchronous Operations | Supported through composition and utilities, potentially requiring more manual setup. | ✓ Natively supported and optimized within the selector API. |
Jotai is designed around a primitive and flexible approach to state management, offering a more atomic model that can feel closer to React's built-in hooks. Its core philosophy centers on providing minimal building blocks that developers can compose to create sophisticated state solutions tailored to their specific application needs. This makes it an excellent choice for developers who prefer fine-grained control and a less opinionated framework, or for those working on projects where performance and bundle size are paramount considerations.
Recoil, on the other hand, presents itself as a dedicated state management library for React, built with a focus on providing a more comprehensive and integrated experience. It aims to simplify state management for complex applications by offering a unified API for atoms (units of state) and selectors (derived state). Its primary audience includes teams that are looking for a robust, battle-tested solution that handles many common state management challenges out-of-the-box, without requiring extensive custom composition.
A key architectural difference lies in their fundamental primitives. Jotai leverages a concept of atoms as the smallest units of state, which are managed independently and can be subscribed to. This allows for highly granular updates and optimized re-renders. Recoil also uses atoms, but its architecture is more centered around a graph-like structure where selectors can efficiently compute derived state based on the current values of atoms, providing a clear distinction between base state and computed state.
Another technical difference surfaces in their approach to derived state and asynchronous operations. While both can handle derived state, Recoil has a more integrated system for selectors that natively supports asynchronous operations and offers built-in caching and memoization for these computations. Jotai also supports derived state and asynchronous operations through its utilities and `useAtom` hook, but it might require more explicit composition of primitives or the use of additional community utilities for complex asynchronous patterns compared to Recoil's built-in selector capabilities.
In terms of developer experience, Jotai often appeals to developers who are comfortable with React's hook-based paradigm and appreciate its minimal API surface. Its close resemblance to `useState` can lead to a gentler learning curve for those already familiar with React. Recoil, while also built for React, introduces its own set of concepts (atoms, selectors, snapshots) which might require a slightly steeper initial learning curve but can lead to more maintainable code in larger, more complex applications due to its structured approach.
Performance and bundle size are significant differentiating factors. Jotai boasts a remarkably small footprint, both in terms of its uncompressed size and its gzipped bundle size, with minimal dependencies. This makes it an attractive option for performance-critical applications or those aiming for the smallest possible client-side bundle. Recoil, while still a capable state management solution, has a larger bundle size and unpackaged footprint, which could be a consideration for applications where every kilobyte counts.
For practical recommendations, choose Jotai if your project prioritizes minimal bundle size, fine-grained control over state, and a developer experience closely aligned with React's core hooks. It's ideal for component libraries, micro-frontends, or applications where adding minimal state overhead is crucial. Opt for Recoil if you are building a large-scale, complex React application and need a robust, integrated solution with built-in support for derived state, asynchronous operations, and a clear separation of concerns.
Regarding ecosystem and maintenance, both packages are actively developed and part of the broader React state management landscape. Jotai's small core makes it highly composable, and its ecosystem often revolves around community-driven utilities that extend its capabilities. Recoil, being an official Facebook (Meta) project, benefits from significant backing and is designed to integrate well within larger React projects, potentially offering a more cohesive experience within that specific ecosystem. Developers should consider the maturity and ongoing support available for each, especially for long-term project commitments.
In terms of niche use cases or emerging trends, Jotai's atomic nature makes it very suitable for advanced patterns like persistent state synchronization across tabs or workers, or for implementing complex undo/redo functionalities with fine-grained state control. Its flexibility allows it to adapt to emerging patterns in React development. Recoil's strength lies in managing complex, interconnected application states where multiple components might depend on overlapping pieces of derived data, ensuring that updates are efficient and predictable across a wide application surface.
CORRECTIONS
Spot wrong data here?Spot wrong data on this page?
A short note helps us fix it.A short note helps us fix it. We read every one; confirmed fixes ship in the next nightly build.
Anonymous · No account · No email back