@rspack/core vs rollup
Side-by-side comparison of @rspack/core and rollup
- Weekly Downloads
- 3.5M
- Stars
- 12.6K
- Size
- 43.2 MB (Install Size)
- License
- MIT
- Last Updated
- 1mo ago
- Open Issues
- 183
- Forks
- 782
- Unpacked Size
- 1.5 MB
- Dependencies
- —
- Weekly Downloads
- 74.5M
- Stars
- 26.3K
- Size
- 170.8 kB (Gzip Size)
- License
- MIT
- Last Updated
- 1mo ago
- Open Issues
- 602
- Forks
- 1.7K
- Unpacked Size
- 2.8 MB
- Dependencies
- 2
@rspack/core vs rollup Download Trends
@rspack/core vs rollup: Verdict
@rspack/core distinguishes itself as a high-performance bundler built from the ground up in Rust, aiming to provide a webpack-compatible API with significantly improved build speeds. Its core philosophy revolves around leveraging the efficiency of Rust to process JavaScript modules and assets, targeting developers and large-scale projects that frequently encounter performance bottlenecks with traditional JavaScript-based bundlers. The primary audience for @rspack/core includes teams seeking to accelerate their development workflows and reduce CI/CD times, especially those already familiar with the webpack ecosystem.
Rollup, on the other hand, is engineered as a next-generation ES module bundler, with a strong emphasis on creating efficient and optimized JavaScript bundles for libraries and modern web applications. Its philosophy centers on producing clean, flat code by leveraging the native ES module system, making it particularly well-suited for libraries that need to support various module formats and environments without runtime overhead. Rollup's target users are often library authors, application developers focused on code splitting, and those prioritizing small, self-contained bundles.
A key architectural differentiator lies in their underlying implementation languages and runtime environments. @rspack/core is written in Rust, allowing it to achieve near-native performance for compilation and bundling tasks, bypassing many limitations inherent to JavaScript execution for such heavy computations. This Rust foundation is critical to its promise of speed. Rollup, conversely, is built and executed within the Node.js JavaScript runtime. While highly optimized through JavaScript, it fundamentally operates within the constraints and concurrency models of V8, which can be less performant for extremely large codebases compared to a compiled language like Rust.
Another technical distinction emerges in their plugin architectures and extension models. @rspack/core strives for webpack compatibility, meaning its plugin API is designed to mirror webpack's, facilitating easier migration for existing webpack users and enabling the use of many webpack-compatible plugins. This approach aims to retain the vast ecosystem of webpack plugins. Rollup features a distinct plugin API that is more opinionated and often requires a different approach to configuration and implementation, generally focusing on transformations and optimizations specific to ES modules. This can lead to a cleaner, more predictable plugin experience for its target use cases.
In terms of developer experience, @rspack/core aims for a familiar feel for webpack users due to its API compatibility, potentially lowering the learning curve for those migrating. Its Rust core might offer quicker build times, indirectly improving the feedback loop during development. Rollup, while also offering a good developer experience, has its own unique configuration patterns and plugin conventions. Developers new to module bundlers might find Rollup's ES module-centric approach more straightforward to grasp for library development, whereas @rspack/core might feel more intuitive for full-stack JavaScript developers accustomed to webpack's broad applicability.
Performance and bundle size considerations present a notable divergence. @rspack/core's Rust implementation is engineered for raw speed, promising significantly faster build times, especially for large projects, by minimizing JavaScript overhead. While its unpacked size is larger at 1.5 MB, this is part of its comprehensive feature set ready for complex builds. Rollup is renowned for producing highly optimized, small bundles, particularly for libraries, due to its efficient tree-shaking and ability to generate minimal output. Its smaller unpacked size (2.8 MB) and specific focus on output optimization make it a strong choice when minimal code, including runtime, is paramount.
For practical recommendations, @rspack/core is an excellent choice when accelerating build times for large, complex front-end applications or monorepos is the primary objective, especially if the project already uses or is migrating from webpack. Its webpack compatibility can ease adoption. Rollup shines when the goal is to bundle JavaScript libraries, create efficient code-split applications where output size is critical, or when a clean ES module-first approach is desired. It is often the default choice for modern library authors.
Migrating from other bundlers to @rspack/core can be relatively streamlined if the project is heavily invested in the webpack ecosystem, given its API compatibility efforts. This reduces potential lock-in to older technologies and offers a path to performance gains. Rollup, while having its own established ecosystem and patterns, does not inherently create significant lock-in. However, transitioning from a Rollup-centric library build to a full-application bundler might require adopting additional tools or a different bundling strategy, whereas @rspack/core aims to cover more of the application bundling spectrum out-of-the-box.
In niche use cases, @rspack/core's Rust foundation might offer opportunities for extremely low-level optimizations or integrations not easily achievable with JavaScript bundlers, potentially benefiting advanced build pipeline tooling. Rollup's strength in producing highly granular, spec-compliant ES modules makes it suitable for emerging JavaScript environments or advanced module experimentations where adherence to standards and minimal footprint are the highest priorities. Both packages continually evolve, with @rspack/core representing a modern, performance-driven approach and Rollup iterating on its core strengths in ES module bundling efficiency.
@rspack/core vs rollup: Feature Comparison
| Criteria | @rspack/core | rollup |
|---|---|---|
| API Compatibility | ✓ Aims for webpack API compatibility to ease migration. | Has a distinct, ES module-centric plugin API. |
| Core Implementation | ✓ Written in Rust for high-performance compilation. | Written in JavaScript, running in the Node.js runtime. |
| Performance Philosophy | ✓ Optimized for build speed through Rust implementation. | Optimized for output code efficiency with ES module focus. |
| Primary Use Case Focus | Accelerating builds for large applications and webpack users. | ✓ Bundling libraries and creating lean application code. |
| Developer Workflow Impact | ✓ Potential for significantly faster build times, improving developer feedback. | Predictable build times, excellent for library development workflows. |
| Extension Mechanism Design | Prioritizes compatibility with existing webpack plugins. | ✓ Offers a more bespoke and purpose-built plugin model. |
| Migration Path Consideration | ✓ Easier migration from webpack projects. | Standard for new library projects, less of a direct migration path from other bundlers. |
| Bundle Output Characteristics | Aims for comprehensive application bundling, potentially larger initial output. | ✓ Excels at generating minimal, highly optimized code for libraries. |
| Ecosystem Integration Strategy | Leverages webpack's vast plugin ecosystem. | ✓ Features its own well-defined and often more opinionated plugin system. |
| Underlying Technology Advantage | ✓ Leverages Rust for concurrency and low-level performance. | Relies on JavaScript's broad accessibility and tooling. |
| Learning Curve for Webpack Users | ✓ Lower for existing webpack users due to API similarity. | Requires learning new configuration paradigms and conventions. |
| Maintainability of Plugin System | May inherit complexities from webpack's plugin model. | ✓ Often perceived as cleaner and more straightforward for its core purpose. |
| Target Project Scale Optimization | ✓ Strongly suited for very large codebases and monorepos. | Ideal for libraries and applications where output size is critical. |
| Rust vs. JavaScript Runtime Performance | ✓ Benefits from native compilation speed of Rust. | Operates within JavaScript runtime constraints, though highly optimized. |