React calls components to calculate the next UI description, then commits necessary DOM changes. A fine-grained reactive system tracks which computations read a changing value and can notify those computations directly. That describes two different ways to organize update work—not a universal performance ranking.
How does React render and commit changes?
React describes a screen update in three stages: trigger, render, and commit. An initial render starts at the root. Later renders can be triggered by a state update in a component or an ancestor.
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- Trigger: An update tells React that the screen may need to change.
- Render: React calls components to determine what the UI should display. For a later render, it calls the component whose state update triggered the work and proceeds through nested output.
- Commit: React applies the DOM operations needed to match the calculated output.
These stages are distinct. A component may run again during rendering even when its resulting DOM is unchanged; React says it leaves unchanged nodes alone and applies only necessary DOM operations. Component execution therefore does not mean that every corresponding DOM node is rewritten. See React’s render-and-commit guide.
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What does fine-grained reactivity mean?
In a fine-grained system, reactive values can track which computations read them. When a value changes, its dependents can be notified so the relevant computations can run, rather than treating component execution as the sole unit of update work.
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Solid’s documentation gives a concrete example. A signal has a getter and setter; reading the getter inside a reactive context establishes a dependency, and writing through the setter notifies dependent computations. Effects run when signals they depend on change. This is Solid’s documented behavior, not evidence about every fine-grained runtime. See Solid’s signals guide and createSignal reference.
Where do the models differ?
| Question | React’s documented model | Fine-grained example: Solid |
|---|---|---|
| What starts update work? | A state update triggers a render. | A signal write notifies computations dependent on that signal. |
| What is re-evaluated? | React calls components to determine the next UI description, proceeding through nested output. | Reactive computations that depend on the changed signal can run. |
| How are dependencies established? | The cited guide describes component rendering and state-triggered updates. | Reading a signal in a reactive context tracks the dependency. |
| What changes in the DOM? | React commits necessary DOM operations; unchanged output can leave nodes untouched. | The cited Solid material explains signal-dependent computations, but does not establish one universal DOM-commit rule for all fine-grained systems. |
The useful comparison is what work each model schedules and how it determines that work. It is misleading to equate React component renders with wholesale DOM replacement, or to assume that every fine-grained system has identical dependency, scheduling, or DOM behavior.
Are virtual DOM rendering and reactivity opposites?
No. Vue documents both a virtual-DOM renderer and reactive dependency tracking, alongside compiler optimizations. These are not necessarily mutually exclusive camps; a framework can combine rendering strategies and reactivity. See Vue’s rendering mechanism guide and reactivity guide.
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The name in the title does not identify a framework, repository, specification, or version. Its update triggers, lifecycle, dependency rules, scheduling, and DOM behavior are therefore not established here. Solid is an illustrative, documented example of fine-grained reactivity; its implementation should not be attributed to the unnamed runtime.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Does fine-grained rendering make an app faster?
Not by itself. The distinction describes where update work is organized, not how quickly a particular application runs. A meaningful performance comparison would need the named runtime, equivalent implementations, a defined workload, and a stated measurement method. No universal speed advantage or benchmark follows from these architectural descriptions.
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