EOL Dataset vs Atlas.new
Side-by-side comparison of features, pros & cons, pricing, and community votes (2026).
🏆 Atlas.new leads with 536 upvotes
Find every EOL dependency in your stack. Free. In 5 minutes.
EOL Dataset is a groundbreaking tool for developers and security teams seeking to understand the lifecycle status of their software dependencies. Unlike traditional SCA tools that focus solely on CVEs and vulnerabilities, EOL Dataset goes a step further by identifying whether dependencies are actively maintained or have reached their end-of-life. By analyzing over 12 million package versions across major ecosystems, the tool leverages official EOL declarations and machine learning to detect maintainer abandonment, providing users with clear insights into which dependencies are still viable. Simply upload a package.json, pom.xml, requirements.txt, or any SBOM, and EOL Dataset delivers precise information about the maintenance status of both direct and transitive dependencies. This makes it an invaluable resource for ensuring software sustainability and reducing technical debt, all at no cost.
Pros
- Provides comprehensive lifecycle status for dependencies across multiple ecosystems
- Utilizes ML-based detection for more accurate maintainer abandonment insights
- Easy to use: upload common dependency files and get instant results
- Free of charge, removing cost barriers for developers and teams
- Helps identify outdated or unsupported dependencies to improve security and stability
Cons
- Focuses solely on maintenance status; does not cover vulnerability scanning or CVEs
- Limited to dependency lifecycle information; may require complementary tools for full security analysis
- Dependence on accurate official EOL declarations, which may vary across ecosystems
Best for
- • Auditing dependencies for active maintenance before production deployment
- • Identifying outdated or abandoned packages to plan for upgrades
- • Assessing the sustainability of open-source components in a project
- • Reducing security risks by replacing unsupported dependencies
Pricing: EOL Dataset is offered as a free tool, making it accessible to individual developers, startups, and larger teams without financial barriers. Its free model allows users to leverage lifecycle insights without subscription costs or usage limits.
The AI agent for maps and spatial data
Atlas.new is an innovative SaaS platform designed to simplify the creation, analysis, and deployment of maps and spatial data. Leveraging AI technology, it enables users—regardless of GIS expertise—to build detailed maps, perform complex spatial analysis, and develop custom spatial applications with ease. Its user-friendly interface and AI-driven automation make spatial data accessible to a broad audience, from data scientists to product managers. By removing traditional barriers associated with GIS software, Atlas.new empowers teams to harness geographic insights quickly and efficiently, making it a valuable tool for businesses and developers seeking to integrate spatial intelligence into their workflows. Its community-driven approach, demonstrated by strong ProductHunt votes, underscores its growing popularity and effectiveness in democratizing geospatial data handling.
Pros
- No specialized GIS skills required, making it accessible to a broad user base
- AI-powered automation simplifies complex spatial analysis
- Intuitive interface facilitates quick map creation and customization
- Supports building and deploying spatial apps seamlessly
- Strong community support with notable user engagement
Cons
- May have limitations for highly advanced GIS professionals seeking in-depth tools
- Pricing details are not explicitly clear, which could affect budget planning
- Dependent on cloud infrastructure, potentially raising data privacy concerns for sensitive projects
Best for
- • Creating interactive maps for marketing and customer engagement
- • Performing spatial analysis for urban planning and development
- • Building location-based services and features into apps
- • Visualizing demographic or environmental data for research
Pricing: Likely follows a freemium model with free access to basic features and paid plans offering advanced capabilities, larger data limits, or enterprise options. Exact pricing details are not specified but are expected to start around a moderate monthly fee.