Kili Technology
The data-centric AI platform for high-quality training data and model evaluation.
The open-standard for unified metadata management, data discovery, and collaborative governance.
OpenMetadata is a comprehensive, open-source metadata management solution that centralizes data discovery, governance, and collaboration. Built on a foundation of JSON-schema-based standards, it treats metadata as a first-class citizen, enabling a consistent and extensible architecture across the data stack. In the 2026 market, OpenMetadata positions itself as the primary alternative to expensive proprietary catalogs by offering native, automated data lineage and integrated data quality profiling. It utilizes a central metadata repository (MySQL/PostgreSQL) and an indexing layer (Elasticsearch/OpenSearch) to provide low-latency discovery. The platform supports over 50+ native connectors, including Snowflake, BigQuery, Databricks, and various BI tools. Beyond simple documentation, OpenMetadata focuses on 'Social Metadata,' allowing teams to collaborate via integrated feeds, tasks, and announcements. Its API-first design ensures that metadata is not a silo but an active participant in data engineering workflows, supporting programmatic updates and automated governance policies. For enterprise-grade scalability, the managed version via Collate provides advanced security, hosted ingestion, and dedicated support, bridging the gap between open-source flexibility and managed service reliability.
Uses JSON Schema to define all metadata entities, ensuring consistent API responses and strict data typing across all services.
The data-centric AI platform for high-quality training data and model evaluation.
The semantic knowledge fabric for high-velocity enterprise intelligence.
Transform complex database schemas into actionable natural language insights with autonomous SQL synthesis.
The industry's first AI-powered, end-to-end data management platform for multi-cloud environments.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Parses SQL query logs and Airflow DAGs to build column-level lineage without manual intervention.
Natively supports Great Expectations-style tests and profiling directly within the metadata service.
Maintains a history of metadata changes, allowing users to see how schemas or descriptions evolved over time.
Activity stream functionality where users can mention others, request descriptions, and assign tasks directly on data assets.
Granular policy engine that controls visibility and edit rights based on user attributes and asset tags.
Triggers external workflows whenever metadata is updated (e.g., notifying Slack when a PII tag is added).
Ensuring all dependencies are understood before moving from On-prem Hadoop to Snowflake.
Registry Updated:2/7/2026
Manually identifying and tagging personally identifiable information across thousands of tables.
Downstream dashboards breaking due to schema changes or data drift.