Community Data

Community Data is a shared database of startup people and companies, aimed chiefly at developers and others working with structured ecosystem data. Its public API and open contribution model make it useful as a data layer; it is less suited to readers who want a finished research product.

Overview

The project describes a database of more than 1 million people and companies, with company profiles and funding data. Its initial emphasis is the startup ecosystem. The data is maintained in an open-source repository and can be queried through a public GraphQL API, so the best fit is for people building applications or consuming data in their own workflows—not those seeking a turnkey directory.

Key features

Structured records and validation

Records are JSON documents organized around schemas for people, companies, locations, sectors, funding stages and curated collections. Every commit is checked against its corresponding JSON Schema, and documents that fail validation cause the commit to be rejected. That provides a consistent structure for contributors and API users, but structural validity does not by itself establish that a record is accurate or complete.

API and contribution model

Anyone can contribute by creating or editing a JSON file in the repository. Developers can query the public GraphQL API and build applications on top of the data; the project also invites them to list those apps in its apps repository. This openness is valuable for teams that want to shape the dataset or tailor an application, but it puts the work of building a useful workflow on the user.

Editor, enhancers and ownership

The project’s editor is a proof-of-concept Next.js application that uses the GitHub API, and contributors authenticate with GitHub accounts. Enhancer scripts can draw on public APIs or websites, structure information to match the canonical schemas and import it into the repository. For person records, Twitter, LinkedIn or a personal website can serve as proof sources. Verified owners are recorded by GitHub username, and pull requests from listed owners are automatically merged without review. That can reduce friction for trusted contributors, but it also makes ownership and account security important considerations.

Governance and license

Schema changes follow a separate route: they are proposed by pull request and reviewed by core contributors during monthly governance calls. The project uses the MIT License, copyright 2025. The distinction between reviewed schema changes and automatically merged owner contributions matters to anyone relying on the dataset’s structure or contributing records.

Pricing

Community Data is free. The Community Data plan costs nothing and includes the open-source database and public GraphQL API. There are no paid tiers or seat charges described, making it a low-cost option for builders who can work with the API and repository. The trade-off is not a cheaper-versus-premium feature split: users should expect to assemble their own applications and workflows.

Platforms

Community Data is available on the web and through an API. API access suits software integrations and custom applications; the web presence and GitHub-based editor support browsing and contributing, with GitHub authentication required for the editor.

Who it's for

Choose Community Data if you are a developer, data consumer or contributor who wants startup ecosystem records in an open, structured format and can make use of a GraphQL API. It is a weaker fit for buyers who need a packaged research interface or a conventional workflow rather than a dataset to query and extend.

Pros and cons

Pros

• Large stated coverage: more than 1 million people and companies gives builders a substantial base for applications focused on the startup ecosystem.
• Open access and contribution: a public GraphQL API and repository contributions let users consume and improve the same dataset without a paid plan.
• Schema checks: commit validation rejects documents that do not conform to the applicable JSON Schema, supporting consistent data structure.

Cons

• Requires a builder’s mindset: the API and repository are data infrastructure, not a finished company research workflow.
• Owner contributions bypass review: verified owners’ pull requests merge automatically, a meaningful governance trade-off for users relying on contributed records.
• Editor is a proof of concept: contributors need GitHub accounts, and the editor’s stated status may not suit teams seeking a mature data-entry interface.

Alternatives

Startup Databases is a useful category starting point if you want to compare options beyond a shared open dataset.

Tracxn is worth considering if you want a freemium alternative with a free trial, mobile and browser platforms, and a Premium plan described as offering unrestricted access, taxonomy, custom reports and analysis.

Discover Startups may suit a startup seeking a dedicated profile visible to investors and media through its free directory plan.

FlareSight is an alternative for company browsing through web and API, with its free plan covering 127,228+ companies, all search filters, five profile views per day, one view-only watchlist and a weekly email digest.

Selva offers a free public view of identity, description and rolled-up totals, with a separate free login tier that adds round structure and dates, a portfolio list and hidden amounts.

StartupDB is another free API-oriented option, offering a database, MCP server and REST API without an account or API key, with 120 requests per minute per IP and no daily cap.

Dealflow.Africa offers free-forever startup access with no credit card required.

Europe Startup Database provides a free account for browsing its database.

The Venture Codex is another database currently offered at no cost.

Verdict

Community Data is a strong choice for developers and data users who want a free, extensible startup dataset with a public GraphQL API and the ability to contribute directly. Its main advantage is open access to structured records at substantial stated scale; its main caution is that verified owners’ contributions are merged without review. Look elsewhere if you need a finished research product rather than a dataset to build on.