EOL Dataset vs Supernova
Side-by-side comparison of features, pros & cons, pricing, and community votes (2026).
🏆 Supernova leads with 333 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- Helps identify outdated or unsupported dependencies to improve security and stability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- • Identifying outdated or abandoned packages to plan for upgrades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.
All your data in Claude and Codex
Supernova is a powerful data integration and AI analysis platform designed for startups and data-driven teams. It connects seamlessly with popular business tools like Stripe, HubSpot, and PostgreSQL, enabling users to quickly access and analyze live data without relying on traditional BI stacks or extensive engineering support. By integrating directly with AI models such as Claude and Codex, Supernova allows anyone in a team to ask complex questions, investigate performance metrics, and perform deep data analyses effortlessly. Its user-friendly approach democratizes data insights, making advanced analytics accessible to non-technical users while maintaining the flexibility needed for sophisticated investigations. This tool is especially valuable for startups seeking rapid insights into revenue, pipeline, customer behavior, and operational metrics, all within the familiar environment of AI-powered interfaces.
Pros
- Easy integration with over 30 popular apps and data sources
- Empowers non-technical team members to perform complex analysis
- Leverages advanced AI models for natural language querying and insights
- Reduces dependency on engineering resources and traditional BI tools
- Real-time data connectivity for up-to-date insights
Cons
- Limited information on pricing and plans available publicly
- May require some setup time to connect multiple data sources
- Potential learning curve for users unfamiliar with AI-powered querying
Best for
- • Analyzing real-time revenue and sales pipeline performance
- • Investigating customer engagement and retention metrics
- • Performing operational analysis without heavy engineering involvement
- • Generating ad-hoc reports using natural language questions
Pricing: Likely operates on a subscription-based model with tiered plans, possibly including a freemium option, but specific pricing details are not publicly available. It appears targeted at startups and small teams seeking accessible data analysis tools.