In the fast-paced world of frontend web development, the way your application automatically reacts to data changes is key. This concept, known as reactivity, is used by frameworks like React through a component-based approach driven by Hooks. However, React is not the only player in the field. As the frontend ecosystem evolves, so do new frameworks and paradigms that aim to challenge the status quo. SolidJS is one such framework that introduces its own solution for managing reactivity and state, known as Signals.
Signals and Hooks, while solving the same problem of reactivity, do so in fundamentally different ways. In this article, we’ll explore how these two approaches emerged, how they differ in their reactivity models, and how developers can evaluate which one best fits their project needs.
Before diving into the differences between Signals and Hooks, it’s important to understand the challenges that existed before these solutions came along.
One of the biggest pain points was state management. Managing state used to be tough; developers often had to rely on manual DOM manipulation and complex patterns to make the UI respond to data changes.
In React’s earlier days, this meant writing verbose class components that used tricky concepts like the this
keyword and higher-order components (HOCs). Handling side effects also required lifecycle methods such as componentDidMount
and componentDidUpdate
, which led to loads of repetitive boilerplate code.
Another issue was wasted re-rendering. There was no efficient way to update only specific parts of the UI, so even small state changes could trigger large, unnecessary re-renders across the application.
These challenges pushed developers to look for a cleaner, more predictable model of state and side effect management, and in 2018, Hooks were introduced.
Hooks, React’s solution to managing state and side effects, introduced a major paradigm shift. Instead of handling logic in class components and lifecycle methods, developers could now manage state and effects directly inside a function. This made code cleaner, more readable, and easier to reason about.
React Hooks also come with two strict rules designed to maintain application stability:
Some of the most commonly used Hooks include:
useState
– This Hook lets a function component remember a value between renders. It returns the current state value and a function that updates it. When the update function is called, React re-renders the componentuseEffect
– This Hook handles side effects, like fetching data or setting up a subscription. It separates “effects” from the main rendering logic, and its cleanup function helps prevent memory leaksSignals represent a different mental model known as fine-grained reactivity, where only specific parts of the UI are updated when there’s a change in the underlying data. Signals can do this because they are built on the observer pattern. In this pattern, when a subject’s value changes, it notifies all the components that are subscribed to it and triggers only the necessary updates, rather than re-rendering the entire application.
SolidJS, known for its highly reactive architecture, places Signals at the core of its fine-grained reactivity model. This model is powered by three main primitives:
createSignal
– Defines a reactive state container that holds a trackable value. When you read a Signal, it subscribes the current effect or memo to that value. When you update it, all subscribed computations are notified and re-run, ensuring the UI stays in synccreateEffect
– Runs automatically whenever any of the Signals it depends on change. It’s responsible for updating the DOM, but unlike React’s re-render cycle, it updates only the specific parts of the UI that depend on that Signal, no unnecessary re-renderscreateMemo
– Computes and caches a derived value based on one or more Signals. Whenever any of its dependencies change, the memo automatically recalculates. This helps avoid redundant computations and keeps your application performant, especially when dealing with frequently changing dataHooks and Signals both offer a way to handle state management in your frontend application as well as a mechanism for handling your application’s side effects:
useState
(Hooks) and createSignal
(Signals), you declare a piece of state and get a function to update it. You don’t have to find a DOM element and change its content manuallyuseEffect
(Hooks) and createEffect
(Signals) provide a dedicated place to handle side effects like data fetching, subscriptions, or manual DOM manipulationsAnother reason Hooks and Signals feel similar is their composability. Both let you create custom, reusable logic that can be shared across different parts of your application. You can build custom Hooks or custom Signals to encapsulate state or behavior and reuse it wherever needed, resulting in cleaner, more maintainable code.
Even their syntax feels familiar, which adds to the sense of similarity from a developer’s perspective.
The main difference between Signals and Hooks is the way that they approach reactivity. Signals focuses on fine-grained reactivity, where components will run only once during the initial render, and updates to the component will be handled by a reactive graph that pushes any updates directly to the part of the UI that depends on that change. Ryan Carniato explains this behavior as Retain Mode in his interview with PodRocket.
Hooks rely on a component-based re-rendering system, where the entire UI is recalculated whenever a state change occurs. This process creates a new virtual DOM tree, which React then reconciles against the previous one to determine what needs to be updated in the real DOM.
Because of this re-rendering model, Hooks must follow strict rules and often require additional effort to prevent performance bottlenecks, especially in larger, data-heavy applications.
They each have their strengths and projects that they are suited for, but at the end of the day, it boils down to choosing between ecosystem and familiarity versus raw performance.
Below is a framework for choosing which strategy to go for with regard to your needs:
Feature | Hooks | Signals |
---|---|---|
Ecosystem & community | Massive. Unmatched library support and community resources make it easy to find solutions and experienced developers. | Smaller but steadily growing. Fewer libraries and resources, which may require building more custom solutions. |
Performance | High, though the Virtual DOM can introduce overhead and unnecessary re-renders in complex, data-heavy apps. | Exceptionally high. Fine-grained reactivity delivers minimal, targeted updates and leads most performance benchmarks. |
Developer experience | Familiar. A large number of developers are already proficient, and the model is well established. | Less familiar. The “component runs once” paradigm can feel new for developers coming from React’s rendering model. |
Best for | Most standard web apps, large teams, and projects where ecosystem and community support are top priorities. | High-performance, data-intensive apps (e.g., dashboards, visualizations, or games) where speed and small bundle size matter most. |
Complexity | Can lead to issues like stale closures if dependencies aren’t managed carefully. | Dependency graphs can grow complex in large projects but are often more predictable than managing useEffect dependencies. |
Both Signals and Hooks provide a far better developer experience than the class-based, imperative patterns of the past. And while there’s plenty of debate about which approach is better, the truth is, there’s no single right answer.
Hooks remain the industry standard for a reason. They’re battle-tested, backed by a massive ecosystem of developers, libraries, and tools, making them the safest and most familiar choice for most teams.
Signals, used in frameworks like SolidJS and Preact, take a fine-grained approach to reactivity, delivering highly efficient updates and smoother user interfaces. For performance-critical or data-heavy applications, they can offer a noticeable edge.
Ultimately, both approaches shine in their own right. The key is understanding the reactivity model behind each and choosing the one that best aligns with your project’s scale, performance goals, and team familiarity.
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