mobx vs. recoil
Side-by-side comparison · 9 metrics · 14 criteria
- Weekly Downloads
- 3.8M
- Stars
- 28.2K
- Gzip Size
- 15.6 kB
- License
- MIT
- Last Updated
- 1y ago
- Open Issues
- 47
- Forks
- 1.8K
- Unpacked Size
- 4.8 MB
- Dependencies
- 1
- 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
mobx vs recoil downloads · last 12 months
Criteria · mobx vs recoil
- API Style
- mobxClass-based and decorator-heavy options, alongside functional approaches.recoil ✓Modern, React hook-centric API (`useRecoilState`, `useRecoilValue`).
- Bundle Size
- mobx ✓Significantly smaller gzipped bundle size.recoilLarger gzipped bundle size compared to MobX.
- State Updates
- mobxUpdates are implicit through observable mutations within actions.recoil ✓Updates are explicit via setters for atoms or by dispatching actions.
- Learning Curve
- mobxPotentially lower for those familiar with OOP, but automaticity can be magical.recoilIdiomatic for React hooks users, but requires understanding the atom/selector graph.
- Core Philosophy
- mobxTransparently functional reactive data flow.recoilA unidirectional data flow graph for global state.
- Boilerplate Code
- mobx ✓Minimal boilerplate, especially with observable decorators.recoilRequires explicit atom and selector definitions, can involve more setup.
- Reactivity Model
- mobx ✓Implicit observable-based reactivity, automatically tracks dependencies.recoilExplicit graph-based reactivity using atoms and selectors.
- State Granularity
- mobxManages state as observable objects and arrays, often more coarse-grained.recoil ✓Manages state as small, atomic units (atoms), encouraging fine-grained state.
- Ecosystem Maturity
- mobx ✓Longer history, more established ecosystem and integrations.recoilNewer, growing ecosystem closely aligned with React's evolution.
- TypeScript Support
- mobxGood TypeScript support, particularly with recent versions.recoil ✓Excellent, first-class TypeScript integration due to its design.
- Debugging Experience
- mobxMature debugging tools available (MobX DevTools).recoilGood debugging support integrated within React DevTools.
- Component Optimization
- mobxAutomatic optimization via dependency tracking; manual `observer` wrapper often needed.recoil ✓Optimized by default due to atomic state and selector memoization.
- Asynchronous Operations
- mobxIntegrated within actions and reactions, less formalized.recoil ✓Formalized through asynchronous selectors, managing loading/error states.
- Derived State Management
- mobxUses computed values which react to observable changes.recoil ✓Uses selectors, which are pure functions operating on atoms or other selectors.
| Criteria | mobx | recoil |
|---|---|---|
| API Style | Class-based and decorator-heavy options, alongside functional approaches. | ✓ Modern, React hook-centric API (`useRecoilState`, `useRecoilValue`). |
| Bundle Size | ✓ Significantly smaller gzipped bundle size. | Larger gzipped bundle size compared to MobX. |
| State Updates | Updates are implicit through observable mutations within actions. | ✓ Updates are explicit via setters for atoms or by dispatching actions. |
| Learning Curve | Potentially lower for those familiar with OOP, but automaticity can be magical. | Idiomatic for React hooks users, but requires understanding the atom/selector graph. |
| Core Philosophy | Transparently functional reactive data flow. | A unidirectional data flow graph for global state. |
| Boilerplate Code | ✓ Minimal boilerplate, especially with observable decorators. | Requires explicit atom and selector definitions, can involve more setup. |
| Reactivity Model | ✓ Implicit observable-based reactivity, automatically tracks dependencies. | Explicit graph-based reactivity using atoms and selectors. |
| State Granularity | Manages state as observable objects and arrays, often more coarse-grained. | ✓ Manages state as small, atomic units (atoms), encouraging fine-grained state. |
| Ecosystem Maturity | ✓ Longer history, more established ecosystem and integrations. | Newer, growing ecosystem closely aligned with React's evolution. |
| TypeScript Support | Good TypeScript support, particularly with recent versions. | ✓ Excellent, first-class TypeScript integration due to its design. |
| Debugging Experience | Mature debugging tools available (MobX DevTools). | Good debugging support integrated within React DevTools. |
| Component Optimization | Automatic optimization via dependency tracking; manual `observer` wrapper often needed. | ✓ Optimized by default due to atomic state and selector memoization. |
| Asynchronous Operations | Integrated within actions and reactions, less formalized. | ✓ Formalized through asynchronous selectors, managing loading/error states. |
| Derived State Management | Uses computed values which react to observable changes. | ✓ Uses selectors, which are pure functions operating on atoms or other selectors. |
MobX is fundamentally built around the concept of observable state and reactions. Its core philosophy is to make state management simple and scalable by minimizing boilerplate code and automatically tracking changes to observable data, triggering re-renders or other side effects only where necessary. This makes it an excellent choice for developers who prefer a more declarative and less explicit approach to state synchronization, particularly within complex applications where manual state updates can become cumbersome. The primary audience for MobX includes React developers seeking a robust yet intuitive way to manage application state, especially those coming from imperative programming backgrounds who appreciate its automaticity.
Recoil, on the other hand, is designed with a more atomic approach to state management in React applications. It offers a core set of building blocks – atoms and selectors – to manage global state. Atoms represent individual pieces of state, and selectors derive state from these atoms or other selectors. This atomic structure is particularly well-suited for scenarios where state can be broken down into numerous small, independent units. Recoil's audience typically comprises React developers who value a modern, hook-based API and a clear separation of concerns for state, often in applications that benefit from fine-grained state updates and memoization.
A key architectural difference lies in their reactivity models and API design. MobX uses a system of observables, computed values, and reactions. You mark your state as observable, and MobX automatically tracks which components or reactions depend on which observables. When an observable changes, only the dependent parts are re-rendered or re-executed. Recoil employs a graph-based approach with atoms and selectors. Atoms are the fundamental units of state, and selectors are pure functions that compute derived state. This explicit graph structure allows Recoil to optimize updates by knowing exactly which parts of the state graph are affected by changes.
Another technical distinction is how they handle asynchronous operations and derived data. MobX often integrates asynchronous operations within actions or reactions, where computed values can react to promises resolving. Recoil has a more formalized way of handling asynchronous queries and derived data through asynchronous selectors. This pattern allows for cleaner integration of data fetching and asynchronous computations directly within the state management graph, providing a built-in mechanism for managing loading and error states associated with these operations.
In terms of developer experience, MobX generally offers a lower barrier to entry for those familiar with object-oriented programming or traditional state management patterns due to its implicit tracking. Debugging can be straightforward with MobX DevTools. Recoil, with its hook-based API (useRecoilState, useRecoilValue, useSetRecoilState), might feel more idiomatic to modern React developers and offers excellent TypeScript support. Its atomic nature can make understanding data flow clear, but managing a large number of atoms and selectors might require more upfront design thinking.
Performance and bundle size considerations show a clear difference. MobX is significantly smaller in its gzipped bundle size, making it a more attractive option for projects where minimizing JavaScript payload is critical. Recoil, while still reasonably sized, is larger and might introduce a slightly more significant overhead. MobX's optimized reactivity system, which precisely tracks dependencies, often leads to efficient re-renders without requiring developers to manually optimize components.
For practical recommendations, if your application has deeply nested components and complex interdependencies where you want state management to largely fade into the background, MobX is often the superior choice. Its automaticity reduces the cognitive load of managing state updates. Conversely, if you are building a modern React application that benefits from a clear, atomic state structure and you prefer explicit management of state dependencies, especially with strong TypeScript integration, Recoil is a strong contender. It excels when state can be naturally segmented.
Regarding ecosystem and long-term maintenance, both packages are well-established and actively maintained within their respective communities. MobX has a longer history and a more mature ecosystem, with various plugins and integrations available. Recoil, being newer, is closely tied to the React ecosystem and benefits from ongoing innovation within React itself, although its ecosystem is still growing. Developers choosing Recoil are betting on its integration with React's future, while MobX offers a proven, stable solution.
Considering niche use cases, MobX's implicit reactivity can be particularly powerful in scenarios involving game development or real-time data visualization where rapid, automatic updates based on complex data structures are essential. Recoil's atomic graph model might be advantageous for applications with highly dynamic UIs where many independent components need to subscribe to specific pieces of state, and precise control over derived state computation is needed. Its selector system is well-suited for complex state transformations and memoization.
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