DataHub

Founded by data industry veterans and backed by LinkedIn, DataHub enables organizations to deploy AI in production through an enterprise-grade metadata platform handling 3M+ PyPI downloads monthly. Leveraging our extensible metadata graph architecture with lineage-driven compliance and API-first design, we've built a unified system for technical teams requiring production-grade discovery, observability, and governance. Our dual solutions—open-source DataHub Core and fully-managed DataHub Cloud—provide what enterprises need for continuous AI & data asset management at scale. DataHub is a unique solution in this space with the following key differentiators:

Scalability: DataHub offers best-in-class enterprise-grade scalability in connecting to over 80 data sources, offering an embeddable connector framework, and ingesting large volumes and high velocity of metadata.

Extensibility: DataHub’s highly extensible metadata model offers easy flexibility in adapting to an organization’s unique data landscape, entities, relationships, ownership, and custom metadata descriptors.

Completeness: DataHub Cloud’s unified platform adds AI-based enhancements and automations for discovery & understanding, quality management, and collaborative governance, allowing users to confidently use and manage data and AI assets.

Ease of Adoption: Customers of DataHub benefit from the joint innovation, peer support, and growing skill base of an energized community of over 13,000 DataHub practitioners. Its user-friendly interface has a powerful and intuitive design, making it easier for users to navigate and utilize its features without extensive training. The managed service of DataHub Cloud offers dedicated support, improved performance and availability, and secure deployment options to ease adoption across an enterprise.

For engineering teams deploying AI in production, DataHub delivers unified metadata infrastructure across all AI & data assets with enterprise-grade performance.