Mental Models of State Management - Jotai/Zustand's Atomic Approach Versus Redux's Single Source
Ethan Miller
Product Engineer · Leapcell

Introduction
In the ever-evolving landscape of front-end development, managing application state efficiently and predictably is paramount. As user interfaces grow in complexity, the challenge of synchronizing data across various components and ensuring a consistent user experience becomes increasingly significant. For years, Redux has been a dominant force, establishing a robust, opinionated pattern for state management centered around a single, immutable store. However, with the advent of React Hooks and a growing emphasis on developer experience and performance, newer libraries like Jotai and Zustand have emerged, offering a different mental model based on atomic state management. This article aims to deeply compare these two distinct paradigms – the atomic approach championed by Jotai and Zustand versus Redux's single-data-flow philosophy – examining their underlying principles, practical implications, and the scenarios where each truly shines. Understanding these differing mental models is crucial for front-end developers to make informed decisions, optimize their applications, and ultimately enhance productivity.
Core Concepts Explained
Before diving into the comparison, let's establish a common understanding of the core terminology that will underpin our discussion.
State Management: The process of organizing and controlling the data that changes within a user interface. Its goal is to ensure consistency, predictability, and reactivity of the UI to data updates.
Single Source of Truth (SSOT): A paradigm where the entire application state is stored in a single, centralized data structure. All changes to this state must go through a well-defined process, typically involving actions and reducers. Redux is a prime example of this model.
Atomic State Management: An approach where state is broken down into smaller, independent, and self-contained units, often referred to as "atoms" or "slices." These atoms can be consumed directly by components, and updates to one atom typically don't directly affect others unless explicitly linked. Jotai and Zustand embody this philosophy.
Reducer: In Redux, a pure function that takes the current state and an action as input and returns a new state. Reducers are the sole way to change the state.
Action: A plain JavaScript object in Redux that describes something that happened in the application. It's the only way to send data to the store.
Store: In Redux, the object that holds the application's entire state tree. It's responsible for allowing access to the state, dispatching actions, and registering listeners.
Selector: A function used to extract specific pieces of data from the global state. In Redux, they are essential for optimizing performance by preventing unnecessary re-renders.
Atom/Slice: In atomic state management, a discrete, independent piece of state. Components subscribe to only the atoms they need.
Principle and Implementation
The fundamental difference between these two paradigms lies in how they conceptualize and manage application state.
Redux and the Single Data Flow
Redux, heavily inspired by Elm, enforces a strict unidirectional data flow. All application state resides in a single JavaScript object (the store). When something needs to change, an "action" is dispatched. This action is then processed by a "reducer," a pure function that takes the current state and the action, and returns a brand new state object. Components then subscribe to relevant parts of this state.
Principle: Predictability and debuggability are at the core. By centralizing state and enforcing strict rules for changes, Redux makes it easier to understand how state transitions occur and to reproduce bugs. Time-travel debugging is a powerful feature stemming from this principle.
Implementation Example:
// Redux Store setup import { createStore } from 'redux'; // Action types const INCREMENT = 'INCREMENT'; const DECREMENT = 'DECREMENT'; // Reducer function counterReducer(state = { count: 0 }, action) { switch (action.type) { case INCREMENT: return { ...state, count: state.count + 1 }; case DECREMENT: return { ...state, count: state.count - 1 }; default: return state; } } // Store const store = createStore(counterReducer); // React Component import React from 'react'; import { useSelector, useDispatch } from 'react-redux'; function Counter() { const count = useSelector(state => state.count); // Select specific part of state const dispatch = useDispatch(); return ( <div> <p>Count: {count}</p> <button onClick={() => dispatch({ type: INCREMENT })}>Increment</button> <button onClick={() => dispatch({ type: DECREMENT })}>Decrement</button> </div> ); }
The Redux ecosystem also includes redux-thunk
or redux-saga
for handling asynchronous operations, further adding to the boilerplate but providing robust ways to manage complex side effects.
Jotai / Zustand and Atomic State Management
Jotai and Zustand, while having their own syntactical differences, share the mental model of atomic state. Instead of one large state tree, you define small, independent pieces of state, or "atoms" (Jotai) / "slices" (Zustand). Components then directly subscribe to these individual atoms or slices. Updates to one atom don't implicitly trigger re-renders in components consuming other, unrelated atoms.
Principle: Granularity and simplicity. The idea is to make state management feel more like using React's useState
hook, but with the ability to share state across components without prop drilling. This leads to less boilerplate, better performance through more targeted re-renders, and a more intuitive developer experience for many.
Jotai Implementation Example:
Jotai focuses on defining derived atoms and keeping the API minimal.
// Jotai Atoms import { atom } from 'jotai'; export const countAtom = atom(0); export const doubleCountAtom = atom((get) => get(countAtom) * 2); // Derived atom // React Component import React from 'react'; import { useAtom } from 'jotai'; function CounterJotai() { const [count, setCount] = useAtom(countAtom); const [doubleCount] = useAtom(doubleCountAtom); return ( <div> <p>Count: {count}</p> <p>Double Count: {doubleCount}</p> <button onClick={() => setCount(prev => prev + 1)}>Increment</button> <button onClick={() => setCount(prev => prev - 1)}>Decrement</button> </div> ); }
Zustand Implementation Example:
Zustand offers a more hook-like API for creating stores, often described as "a small, fast, and scalable bear-necessities state-management solution."
// Zustand Store import { create } from 'zustand'; export const useCounterStore = create((set) => ({ count: 0, increment: () => set((state) => ({ count: state.count + 1 })), decrement: () => set((state) => ({ count: state.count - 1 })), })); // React Component import React from 'react'; import { useCounterStore } from './store'; function CounterZustand() { const count = useCounterStore((state) => state.count); // Selector for specific state const increment = useCounterStore((state) => state.increment); const decrement = useCounterStore((state) => state.decrement); return ( <div> <p>Count: {count}</p> <button onClick={increment}>Increment</button> <button onClick={decrement}>Decrement</button> </div> ); }
Both Jotai and Zustand shine in their capability to make state management feel local and intuitive, much like React's own useState
, but extended to be shareable globally. They often achieve better performance out-of-the-box due to their granular subscription model.
Application Scenarios
The choice between these paradigms often depends on the project's scale, complexity, and the team's preference.
When Redux (Single Data Flow) is a Strong Fit:
- Large, Complex Applications: When the application's state interactions are intricate, and deep predictability and traceability are critical. The explicit action-reducer cycle provides a clear audit trail.
- Highly Collaborative Teams: The strict patterns and large ecosystem around Redux can make it easier for many developers to onboard and contribute consistently to a large codebase.
- Need for Centralized Debugging Tools: Redux DevTools are unparalleled for time-travel debugging, action replaying, and state inspection, which are invaluable for complex state interactions.
- Strict Immutability Requirements: Redux inherently enforces immutability, which can prevent subtle bugs related to state mutation.
- Complex Asynchronous Workflows: With middleware like Redux Saga or Thunk, Redux offers powerful and battle-tested solutions for managing intricate asynchronous operations.
When Jotai/Zustand (Atomic State) is Preferred:
- Small to Medium-Sized Applications: For projects where the state graph is less interconnected and the primary goal is to share simple state between components without much overhead.
- Performance-Critical Applications: Their fine-grained re-rendering mechanisms often lead to better performance out-of-the-box due to more targeted updates. Components only re-render when the specific atom/slice they subscribe to changes.
- Developer Experience and Simplicity: They offer a more "React-ish" and less boilerplate-heavy approach, making them quicker to learn and integrate, especially for developers familiar with
useState
anduseContext
. - Micro-Frontends or Feature-Sliced Architectures: Their atomic nature lends itself well to architectures where different parts of the application might manage their state independently.
- Need for Derived State: Both Jotai (through derived atoms) and Zustand (through selectors or computed properties) make it straightforward to create derived state that updates efficiently when dependencies change.
- Avoiding "Over-Engineering": For projects that don't require the full power and strictness of Redux, these libraries offer a lighter, more agile solution that can prevent unnecessary complexity.
Conclusion
Both the single-data-flow paradigm exemplified by Redux and the atomic state management approach of Jotai and Zustand offer powerful solutions for front-end state management. Redux provides a highly predictable, traceable, and robust system ideal for large-scale applications with complex state interactions and large teams, often at the cost of boilerplate. Conversely, Jotai and Zustand prioritize developer experience, simplicity, and granular performance through their atomic model, making them excellent choices for many modern React applications, especially when a lighter, more direct approach is desired. Ultimately, the choice hinges on the specific needs of your project, balancing the demands of predictability and debuggability against simplicity and performance.