datavanat

Datavanat is a data management and analytics platform designed to unify data access, governance, and analytics across diverse sources. It combines data virtualization, metadata management, and policy-driven governance to support self-serve analytics while preserving control over data.

The architecture is modular, with a data access layer that federates queries, a processing layer for transformations, and a presentation layer for reporting. It includes a centralized metadata catalog, data lineage, and policy-based access controls.

Origin and development: the term and project emerged in 2023 as a collaborative effort among data-science researchers and industry practitioners under the Datavanat Initiative. A reference implementation and documentation followed in 2024.

Key features include SQL, Python and API access; data virtualization; automatic lineage and impact analysis; quality checks; role-based access control with masking; connectors to databases, data lakes, and messaging systems; and a plugin system for transformations.

Use cases include cross-system analytics, enterprise data platforms, data sharing within organizations, and collaborative research, with attention to performance, caching, and incremental refresh strategies.

Reception and limitations: as an open reference project, datavanat is praised for unifying data access but criticized for complexity and the potential for vendor lock-in with some ecosystem connectors.

Related topics include data catalog, data lake, data mesh, and data virtualization.