d3 vs visx

data-viz

visx

D3.js is the foundational low-level library for data-driven DOM manipulation, offering complete control over SVG, Canvas, and HTML rendering with a functional, framework-agnostic API. visx is a collection of React component primitives built on top of D3's mathematical utilities, designed specifically to avoid D3's imperative DOM manipulation patterns in favor of declarative React patterns.

This comparison matters because choosing between them fundamentally depends on your framework context and abstraction preference. D3 developers work directly with selections, enter/update/exit patterns, and have granular control over every pixel. visx developers compose reusable React components like , , and that handle rendering while D3 calculates scales and shapes behind the scenes. Both serve data visualization needs but represent different philosophies: raw power versus React-idiomatic convenience.

Head-to-Head

React Integration→ visx wins

Requires manual lifecycle management and DOM manipulation that fights React's declarative model. You must handle enter/update/exit patterns in useEffect hooks, manage refs for D3 selections, and carefully orchestrate when D3 touches the DOM versus when React does. This creates maintenance overhead and potential conflicts.

visx

Purpose-built for React with declarative component APIs. All primitives are React components that accept props and handle their own rendering. No need to manage D3 selections or lifecycle conflicts—you compose visualizations using standard React patterns like state, props, and hooks. The DOM is entirely controlled by React.

Customization Depth→ d3 wins

Offers complete control over every aspect of rendering, from custom interpolators to pixel-perfect animation tweening. You can manipulate any DOM attribute, create entirely novel visualization types, and implement complex interactions with full access to D3's transition system, force simulations, and geographic projections.

visx

Provides pre-built primitives (arcs, lines, areas, scales) that cover common chart types but abstracts away D3's lower-level capabilities. Custom visualization types require either combining existing primitives or dropping down to D3 directly. Animation and advanced features like force layouts aren't wrapped—you'd use D3 alongside visx.

Learning Curve→ visx wins

Steep learning curve requiring understanding of selections, data joins, enter/update/exit patterns, and functional composition. The API is powerful but verbose, with concepts like `selectAll().data().join()` that take time to internalize. Documentation is comprehensive but examples often require significant adaptation for real projects.

visx

Significantly gentler for React developers already familiar with component composition. The API maps directly to React concepts—props for configuration, children for composition. You still need to understand scales and coordinate systems, but avoid D3's imperative patterns entirely. Component docs include clear prop tables and straightforward examples.

Bundle Size Flexibilitytie

Highly modular with separate packages for every feature (d3-scale, d3-shape, d3-axis, etc.). You can import only what you need, potentially keeping bundles very small. However, many real-world visualizations require multiple modules, and the full D3 bundle is around 240KB minified, though tree-shaking helps significantly.

visx

Also modular with scoped packages (@visx/scale, @visx/shape, @visx/axis) but includes React component overhead on top of D3's math utilities. Each visx component wraps D3 calculations with React rendering logic. For simple charts, visx bundles may be slightly larger, but the difference narrows as complexity grows since you're not including D3's DOM manipulation code.

TypeScript Experience→ visx wins

Community-maintained types via @types/d3 that are comprehensive but sometimes lag behind library updates. Type inference can be tricky with chained selections and generic data types. You often need explicit type annotations for selections and data joins, and complex transformations may require type assertions.

visx

Written in TypeScript with first-class type support. All components have complete prop type definitions, scales are properly typed, and generics work intuitively with your data shapes. IDE autocomplete and error checking are excellent. Type safety extends through the entire component tree without manual annotation.

Framework Portability→ d3 wins

Completely framework-agnostic—works with vanilla JS, React, Vue, Angular, Svelte, or any environment with a DOM. The same D3 code can be reused across projects regardless of framework choice. This makes it ideal for shared visualization libraries, embedding in diverse applications, or long-term projects that might migrate frameworks.

visx

Locked to React—components only work in React environments. If your project uses Vue, Angular, or might migrate away from React, visx code cannot be reused. This dependency risk is significant for library authors or teams with mixed framework stacks. The tight coupling is the tradeoff for better React ergonomics.

Verdict

Choose visx if you're building data visualizations in a React application and want to work with React patterns rather than against them. The productivity gain from declarative components, TypeScript support, and elimination of lifecycle conflicts outweighs the slight reduction in low-level control for most standard chart types (line charts, bar charts, scatter plots, pie charts, heatmaps). You'll write less code, onboard teammates faster, and maintain consistency with the rest of your React codebase. visx is the pragmatic choice for 80% of React-based dashboard, analytics, and reporting interfaces.

Choose D3 if you need framework independence, are creating novel visualization types that don't fit standard chart primitives, or require D3's advanced features like force simulations, complex geographic projections, or intricate custom animations. Also choose D3 if you're working outside React entirely—it remains the only serious option for framework-agnostic visualization libraries. The learning investment pays off when you need that last 20% of control that component abstractions can't provide, or when your visualization needs to run in vanilla JS, Vue, Angular, or server-side environments.

When to Use Each

If you are building a React analytics dashboard with standard chart types (lines, bars, areas, pies) → use visx because you'll leverage existing React patterns, get TypeScript safety, and avoid fighting React's rendering model with imperative D3 selections.

If you are creating a novel network visualization with custom force-directed layouts and particle animations → use d3 because visx doesn't wrap D3's force simulation or complex animation systems, and you'll need the low-level control D3 provides for custom behaviors.

If you are building a charting library that must work across Vue, React, and Angular applications → use d3 because it's framework-agnostic, allowing you to maintain one codebase that renders visualizations regardless of the consuming framework.

If you are prototyping interactive data stories in a React app with tight deadlines → use visx because the component-based API lets you compose charts rapidly without mastering D3's enter/update/exit patterns, and the TypeScript support catches errors during development.

Learn More

d3 →visx →

Head-to-Head

React Integration→ visx wins

visx

Customization Depth→ d3 wins

visx

Learning Curve→ visx wins

visx

Bundle Size Flexibilitytie

visx

TypeScript Experience→ visx wins

visx

Framework Portability→ d3 wins

visx

Verdict

When to Use Each