Performance considerations and optimizations for CSS-in-JS

Anton Ioffe - November 9th 2023 - 11 minutes read

In the relentless quest for optimal web performance, we're constantly reconciling the convenience of abstraction with the raw speed of execution. As we venture deeper into the nexus of design and functionality through CSS-in-JS libraries, developers are often caught in a tangle of style rendering that could silently strangle page efficiency—unless approached with surgical precision. In this article, we'll unravel these performance threads, moving beyond mere implementation to mastery of execution. From dissecting the intricacies of dynamic styling overhead to exploring the cutting-edge of zero-runtime CSS solutions, our journey uncovers the sophisticated techniques and patterns that seasoned developers employ to ensure their applications not only look sharp but also operate with aerodynamic speed. Strap in for an advanced expedition through the optimization landscape of CSS-in-JS, where performance is not just a metric, but an art form.

Harnessing CSS-in-JS Efficiency: Advanced Performance Techniques

CSS-in-JS libraries have thrived by promoting styles encapsulation within components, thus ensuring modularity and collision avoidance. However, the gravitas of performance implications they carry cannot be overstated, particularly in hefty, interactive applications. Strategic application and discernment in the deployment of CSS-in-JS are pivotal, demanding a consideration of the computational cost and DOM management in tandem with the application's dynamic performance needs.

Runtime style generation, a common trait in CSS-in-JS, might lead to excessive computation and a bloated DOM. This scenario escalates with an increasingly complex or numerous set of components needing concurrent updates. To tackle this, developers should employ performance-oriented strategies like memoization to cache styled components, or apply throttling to style computations in response to rapid prop changes. Here’s a more performance-centric example:

// Memoized style generator prevents unnecessary recalculations
const generateButtonStyles = memoize((variant) => {
    return {
        backgroundColor: variant === 'primary' ? '#007bff' : '#6c757d',
        border: variant === 'primary' ? '1px solid #007bff' : '1px solid #6c757d',
        // Memoization ensures this object is reused between renders

// Button component, using memoized styles for improved performance
function Button({ variant, children }) {
    const buttonStyles = generateButtonStyles(variant);
    return <button style={buttonStyles}>{children}</button>;

In line with CSS specificity and the contest for style dominance, a prudent practice is to sidestep overcomplicated nested selectors. Instead of inheritance, adopt composition at the style level, assembling, and applying discrete style objects as needed. This practice preserves rendering velocity and scales back the complexity of managing CSS dependencies.

A conscientious approach to CSS-in-JS demands a continuous honing of techniques—deploying memoization, throttling style recalculations, and understanding the underpinnings of style injection in component lifecycles. Meticulous planning and performance literacy serve as the building blocks for a responsive and scalable front-end architecture. By bearing in mind these principles, we can achieve an equilibrium where our CSS-in-JS not only enriches the developer experience but also aligns with the high-speed efficiencies expected in modern web applications.

The Overhead of Dynamic Styling

Dynamic styling with CSS-in-JS libraries introduces a non-trivial overhead to web applications, particularly in the realm of runtime performance and memory management. As components mount or update, these libraries generate and inject <style> tags into the DOM, each containing potentially unique class definitions that mirror the current state of the component's props. This dynamic process taxes the browser's engine each time a new class is created or an existing class is updated, leading to more frequent style recalculations and layout reflows. With numerous components on the page, this can lead to a significant increase in the time it takes for the browser to compute layouts and apply styles, thereby extending the critical rendering path and potentially delaying meaningful paint times.

Memory usage is another consideration when working with dynamic styles. The styles for each component foster the accumulation of <style> tags that persist in the DOM, even for component instances that are no longer active. While these tags contain classes that are not transmitted over the network, their presence still occupies memory and contributes to a larger DOM size. The decision to leave these tags in place is commonly made to evade the cost of DOM manipulation, which can include expensive operations like reflows. However, the sustained growth of unused styles can lead to inflated memory usage, particularly in single-page applications that may continually add and remove components as the user navigates through the app.

The runtime cost of injecting these styles is magnified as applications scale. While CSS-in-JS libraries offer isolated scope to avoid style collisions, they inadvertently increase complexity in the CSS specificity and cascade. Dynamically generated styles typically yield specific, hashed class names that can override global styles and create intricate layers of specificity. When components adjust to state changes, the injected classes alter the cascade, potentially leading to costly recalculations as the browser resolves conflicts among competing styles.

Moreover, dynamic styling can incur indirect costs in terms of debugging and maintainability. When styles are entangled with component logic, developers might find it challenging to trace back the source of a particular style, as it may not be statically analyzable outside the context of the component's runtime state. The injected classes can clutter DevTools, obscuring the mapping between elements and their styles. These factors increase cognitive load and can lead to longer development cycles, compounding the direct performance costs.

CSS-in-JS Profiling and Benchmarking

When profiling and benchmarking CSS-in-JS, accurate measurement of real-world examples is crucial. To commence, utilize the Chrome DevTools Performance Monitor as it reveals real-time CPU usage, layouts per second, style recalculations per second, and other vital indicators that signify the performance overheads of CSS-in-JS libraries. By initiating a recording session while navigating through common user interactions, developers can identify and analyze render times comprehensively. Ensuring that these measures are taken in both development and production environments is essential, as optimizations in build tools and minification can influence the performance characteristics significantly.

A paramount metric to scrutinize is render time, which directly impacts user-perceived performance measures such as First Contentful Paint (FCP) and Largest Contentful Paint (LCP). These metrics reflect the time taken for the browser to render the first piece of DOM content and the largest content element visible within the viewport, accordingly. These are especially pertinent for CSS-in-JS as styling is often applied via JavaScript, which can extend critical rendering paths. Leveraging the Performance panel in DevTools allow developers to record and dissect activities in a session, thereby enabling the pinpointing of paint and rendering bottlenecks that could be related to CSS-in-JS usage.

In scenarios with intense UI dynamism, where large datasets and frequent UI updates are common, profiling becomes indispensable. For such use cases, observing the Performance panel during stress tests can expose performance hits. For instance, rapidly changing component states that trigger re-renders can lead to spikes in layouts/sec and style recalcs/sec. Developers should precisely note these occurrences, as they are markers for optimization opportunities. It is wise to analyze these reports in the context of the overall user experience, assessing how much these render times actually affect the FCP and LCP, and thus the perceived responsiveness of the application.

Lastly, it is beneficial to examine the Chrome DevTools Coverage panel to ascertain the amount of CSS being utilized by the application. While CSS-in-JS strives to inject styles that are immediately needed, there's a risk of generating unused styles, leading to inflated CSS delivery that hampers performance. Auditing this in real-time user interactions helps in uncovering inefficiently injected styles or redundancies. By iteratively refining the styling logic based on coverage data, developers can optimize the critical rendering path—striking a balance between stylistic dynamism and performant user experiences. This meticulous approach to profiling and benchmarking reaffirms the developer's commitment to not only the functionality but the seamless performance of the application at hand.

Optimizing CSS-in-JS at Runtime

Optimizing your CSS-in-JS runtime involves strategic trade-offs to mitigate performance costs while maintaining the benefits of styling in JavaScript. Memoization, a standard optimization technique, can be particularly effective. Take, for example, a styled component that receives frequently changing props; memoizing this component will ensure that the generated style object is reused whenever the props remain unchanged, reducing unnecessary computations. The same principle can be applied to theme objects or other prop dependencies to avoid rerendering due to shallow prop changes. This approach not only saves time during render but also prevents unnecessary allocations of memory for new style objects.

import React, { useMemo } from 'react';
import styled from 'styled-components';

const StyledButton = styled.button`
  background-color: ${props => props.theme.main};
  color: white;

const Button = ({ theme, label }) => {
  const memoizedStyle = useMemo(() => ({ main: theme.main }), [theme.main]);

  return <StyledButton theme={memoizedStyle}>{label}</StyledButton>;

Another optimization is to leverage atomic CSS generation. By breaking down styles into unique atomic classes that correlate to single style rules, you can greatly reduce the amount of CSS generated. Rather than creating a new class for every style permutation, reuse existing atomic classes. This technique minimizes the generated stylesheet's size and mitigates the risk of flooding the DOM with excessive style tags, which can slow down page rendering and lead to DOM thrashing.

Refactoring components to minimize rerenders is also crucial. Excessive rerenders can lead to style recalculations and layout thrashing. Therefore, carefully architecting your components to only rerender when necessary is key. Avoid deep component trees that pass down style-related props, and consider using React's memo higher-order component or shouldComponentUpdate lifecycle method to control whether a rerender should occur based on prop changes.

import React, { memo } from 'react';
import styled from 'styled-components';

const StyledListItem =`
  font-size: ${props => props.fontSize}px;

const ListItem = memo(({ fontSize, text }) => (
  <StyledListItem fontSize={fontSize}>{text}</StyledListItem>
), (prevProps, nextProps) => {
  return prevProps.text === nextProps.text && prevProps.fontSize === nextProps.fontSize;

Dynamic extraction can also be an asset. By extracting static styles at compile time and only dynamically injecting styles that truly need to be dynamic (e.g., based on state or props), you reduce runtime overhead. This not only improves performance by minimizing the need for runtime style computations but also results in cleaner code, as the separation between static and dynamic styles becomes more apparent.

The combination of these techniques—memoization, atomic CSS, controlled rerenders, and dynamic extraction—can lead to a significant performance boost for your application. Moreover, they exemplify best practices for writing efficient, maintainable CSS-in-JS that scales with your project. Have you audited your CSS-in-JS for these optimizations, and what impact did it have on your rendering performance?

Reusability and Composition in CSS-in-JS

In the realm of CSS-in-JS, reusability hinges on the art of composing styles without overburdening the resulting components. When crafting a UI library with CSS-in-JS, a common temptation is to deeply compose styled components. However, this can be detrimental, creating an intricate web of dependencies that hampers both performance and modularity. Instead, consider leveraging utility functions that encapsulate common styles. For instance, using a css prop could enable you to mix snippets of predefined styles, achieving the same effect as composition without bloating the component tree. This approach minimizes the overhead introduced by numerous Context consumers inherent in some libraries.

When establishing a component hierarchy, prefer to use higher-order components (HOCs) with caution. An effectively designed HOC can facilitate the reuse of logic across your components, as well as theme consistency. For example:

const withCommonStyles = (WrappedComponent) => (props) => (
  <WrappedComponent {...props} className={`common-styles ${props.className}`} />

This HOC injects a base class that includes shared styles, thus abstracting repeated CSS declarations. Nonetheless, be wary of over-using HOCs, as they can obscure the origins of props, leading to difficult-to-trace bugs and, sequentially, a decline in maintainability.

When debating the pros and cons of composition in styled-components and emotion, it's crucial to scrutinize the trade-offs between dependent and independent styles. As styled-components dynamically create classes, the act of extending components like in the case of styled(ExistingComponent) can reduce the number of generated classes, offering a flatter inheritance structure that is performance-friendly. On the contrary, each extension generates a new class, potentially leading to an expansive stylesheet. Utilizing primitive building blocks from a library like emotion, you can carve out composable units that cater to your components' specific needs without overextending the underlying styled instances. This method preserves the clarity of your component's purpose, reducing the tendency for unintended prop collisions.

A best practice is to define a clear, concise set of utility styling functions that encapsulate frequent patterns, thus promoting reusability without the overhead. In the Emotion library, styled components can be leaner thanks to the composition of css tagged templates. Alongside the compositional pattern, maintaining a separation of concerns by delineating 'smart' container components from 'dumb' presentational ones reinforces this practice:

import { css } from '@emotion/react';

const baseButtonStyles = css`
  padding: 10px;
  border: none;
  cursor: pointer;

const primaryButtonStyles = css`
  background: blue;
  color: white;

const PrimaryButton = (props) => (
  <button css={primaryButtonStyles}>{props.children}</button>

In the above example, styling is centered around functional pieces that coalesce to form a PrimaryButton without unnecessary complexity. Through these strategies, we achieve a balance, enhancing reusability while maintaining a vigilant eye on the performance-and-complexity spectrum.

Zero-runtime CSS-in-JS and Static Extraction

Zero-runtime CSS-in-JS libraries offer a compelling alternative to the runtime-based alternatives by shifting much of the work to compile-time. This paradigm change manifests in the generation of static CSS files during the build process, as opposed to creating style tags or injecting CSS at runtime. This architectural approach cuts down on client-side computations and leads to faster rendering times since the browser no longer has to parse and apply styles on the fly. However, one needs to consider the trade-offs: zero-runtime solutions may lead to a less dynamic styling experience and potentially more effort during development to handle dynamic styling scenarios, as changes in the component's state won't automatically propagate to the CSS without additional configuration.

The performance benefits of a zero-runtime approach are notable, particularly for high-traffic applications where milliseconds matter. By converting styles to static CSS at build time, we avoid the costly DOM manipulation of inserting or updating style tags. This not only reduces the amount of JavaScript needed to run on the client but also shrinks the bundle size significantly. On the flip side, these optimizations might add complexity to the build toolchain and require developers to adapt to a more rigid workflow where styles are less intertwined with component logic.

Developer experience (DX) with zero-runtime libraries can be a mixed bag. The static extraction process can streamline the development by reducing the cognitive load associated with managing dynamic styles and potential side effects. However, these libraries might lack some of the developer-friendly features that runtime-based solutions offer, such as hot reloading of styles or context-aware theming. As such, while the developer might benefit from improved performance and simpler debugging, they might miss some of the flexibility that runtime-based libraries provide.

When considering migrating towards a zero-runtime CSS-in-JS architecture, a phased approach is often most effective. Begin by identifying and converting the most "static" components, whose styles do not rely on state or props for their definition. Over time, migrate more complex dynamic components by abstracting theme data and state dependencies to minimize reliance on runtime style computations. This not only allows for incremental improvement in performance but also smooths the transition for the development team by allowing them to adapt to the new workflow and addressing potential challenges piece by piece.


This article explores performance considerations and optimizations for CSS-in-JS in modern web development. It highlights the potential overhead and challenges of dynamic styling, and provides strategies for improving performance, such as memoization and atomic CSS. The article also emphasizes the importance of profiling and benchmarking CSS-in-JS, and suggests techniques for optimizing runtime performance. It discusses the benefits of reusability and composition in CSS-in-JS, and introduces the concept of zero-runtime CSS-in-JS libraries. The key takeaway is that by employing these techniques and approaches, developers can achieve optimal performance while leveraging the power and flexibility of CSS-in-JS. A challenging technical task for the reader would be to identify potential performance bottlenecks in their own CSS-in-JS implementation and implement one or more of the optimizations discussed in the article.