COMPARISON · LINTING & FORMATTING

dprint-node vs. oxlint

Side-by-side comparison · 9 metrics · 14 criteria

dprint-node v1.0.8 · MIT
Weekly Downloads
1.5M
Stars
490
Size
24.8 MB (Install Size)
License
MIT
Last Updated
3y ago
Open Issues
13
Forks
11
Unpacked Size
24.8 MB
Dependencies
N/A
oxlint v1.86.0 · MIT
Weekly Downloads
23.3M
Stars
22.9K
Size
70 B (Gzip Size)
License
MIT
Last Updated
7mo ago
Open Issues
939
Forks
1.3K
Unpacked Size
2.4 MB
Dependencies
1
DOWNLOAD TRENDS

dprint-node vs oxlint downloads · last 12 months

Download trends for dprint-node and oxlint2 download series from Oct 2025 to Sep 2026. Use left and right arrow keys to inspect monthly values.022.7M45.5M68.2M91.0MOct 2025JanAprJulSep 2026
dprint-node
oxlint
FEATURE COMPARISON

Criteria · dprint-node vs oxlint

Core Technology
dprint-node
Implemented in TypeScript/JavaScript for Node.js execution.
oxlint ✓
Core engine written in Rust for maximum performance.
Target Audience
dprint-node
Developers needing programmatic formatting control in Node.js.
oxlint
Developers prioritizing rapid, comprehensive code analysis.
Primary Function
dprint-node
Provides a programmatic API for code formatting.
oxlint
Offers high-speed code linting and analysis.
Performance Focus
dprint-node
Performance is a feature, but secondary to formatting control.
oxlint ✓
Performance is a core design principle, optimized for speed.
Scope of Analysis
dprint-node
Focuses on code style and formatting enforcement.
oxlint ✓
Broader scope including linting, error detection, and potential optimization hints.
Extensibility Model
dprint-node
Configurable via files, with programmatic API for customization.
oxlint
Supports configuration files and potentially plugins for extended functionality.
API vs. CLI Emphasis
dprint-node ✓
Strong emphasis on a well-defined Node.js API.
oxlint
Strong emphasis on a performant CLI, with API potential.
Integration Approach
dprint-node ✓
Designed for deep integration into Node.js build tools and scripts.
oxlint
Primarily a CLI tool, with potential for programmatic use.
Architecture for Speed
dprint-node
Leverages Node.js runtime, performance is good but not its primary focus.
oxlint ✓
Compiled Rust core designed from the ground up for raw speed.
Bundle Size Efficiency
dprint-node
Larger unpacked size due to Node.js runtime dependencies.
oxlint ✓
Extremely small bundle size (70 B gzip), optimized for minimal footprint.
Developer Feedback Loop
dprint-node
Feedback integrated via build process or IDE hookpoints.
oxlint ✓
Near-instantaneous feedback via fast CLI execution.
Codebase Size Consideration
dprint-node
Suitable for projects where formatting is a controlled aspect of the build.
oxlint ✓
Highly advantageous for very large codebases due to speed.
Learning Curve for Integration
dprint-node ✓
Low for Node.js developers needing to script formatting.
oxlint
Moderate if advanced programmatic use beyond CLI is desired.
Toolchain Consolidation Potential
dprint-node
Primarily a formatter, complementing other tools.
oxlint ✓
Offers linting, parsing, and minification, potentially reducing toolchain complexity.
VERDICT

dprint-node offers a programmatic API for the dprint code formatter, primarily designed for integrating its robust formatting capabilities into custom workflows and build processes within Node.js environments. Its core philosophy centers on providing a reliable and performant code formatting solution that developers can leverage programmatically, making it ideal for build tools, IDE integrations, and CI/CD pipelines where automated code style enforcement is paramount. The primary audience for dprint-node includes developers who need fine-grained control over code formatting as part of their development tooling, rather than direct end-user application.

oxlint, on the other hand, is a high-performance linter built for speed, leveraging Rust for its core engine. It aims to provide extremely fast code analysis and linting, making it suitable for large codebases and development workflows where immediate feedback is crucial. Its design philosophy prioritizes developer productivity through rapid detection of code quality issues and potential bugs, positioning it as a powerful tool for teams seeking to maintain code health and consistency at scale. The target audience is developers and teams prioritizing speed and comprehensive static analysis in their JavaScript and TypeScript projects.

A key architectural difference lies in their primary function and exposure. dprint-node is fundamentally an API for a formatter, exposing functions to format code strings or files. Its architecture is built around enabling other tools to call its formatting logic. oxlint, conversely, is a standalone linter application that also exposes a command-line interface, with its speed derived from its compiled Rust core and efficient parsing. While dprint-node is about applying a consistent style programmatically, oxlint focuses on analyzing code for errors and style violations.

Another significant technical divergence is in their approach to extensibility and configuration. dprint-node's configuration is typically managed via a dedicated configuration file (e.g., `dprint.json`), and its Node.js API allows for programmatic configuration overrides. It's designed to be opinionated yet configurable to a degree that satisfies diverse project needs. oxlint, while also supporting configuration files, presents a broader scope by including parsing and minification capabilities alongside linting. Its speed is a core architectural advantage, achieved through its compiled nature, which contrasts with dprint-node's reliance on the Node.js runtime for its API execution.

From a developer experience perspective, dprint-node excels in scenarios where deep integration into a build system is required, offering a predictable API for formatting tasks. Its learning curve is relatively shallow for developers already familiar with Node.js scripting. oxlint, with its command-line focus and emphasis on speed, offers immediate feedback during development, potentially reducing the time spent waiting for linter results. Its rapid execution can feel more responsive, though deep programmatic integration might be less straightforward than dprint-node's dedicated API.

Performance and bundle size are notable differentiators. oxlint boasts an exceptionally small bundle size (70 B gzip) and significantly faster execution times due to its Rust implementation, making it highly efficient. dprint-node, being a Node.js API that wraps a formatter, has a larger unpacked size (24.8 MB) and its performance is bound by the Node.js runtime's capabilities for executing JavaScript. For applications where minimizing toolchain overhead and maximizing execution speed is critical, oxlint presents a compelling advantage.

In practical terms, choose dprint-node when your primary need is to integrate automated, consistent code formatting into your existing Node.js build pipelines, IDEs, or custom scripts. It’s ideal for enforcing stylistic consistency programmatically. Opt for oxlint when you require a high-speed linter that catches a wide array of potential issues quickly, especially in large projects where linter performance directly impacts developer iteration time. oxlint's speed and comprehensive analysis make it suitable for proactive code quality management.

Considering the ecosystem and maintenance, dprint-node benefits from being part of the dprint ecosystem, which aims for broad language support through plugins. Its Node.js API makes it a natural fit for JavaScript and TypeScript projects already invested in the Node.js tooling landscape. oxlint, as a rapidly evolving tool with a strong focus on performance, suggests a trajectory towards becoming a go-to linter for speed-conscious developers. Its Rust foundation implies potential long-term performance benefits and maintainability.

For niche use cases, dprint-node's programmatic API makes it adaptable for generating formatted code snippets on the fly or within complex code generation tools. oxlint's broad feature set, touching on compilation and minification alongside linting, might appeal to developers looking for a consolidated tool for static analysis and code optimization, potentially reducing the number of individual tools needed in a project's setup.

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