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Submission declined on 3 June 2026 by Helpful Raccoon (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content. LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. These tools are prone to specific issues that violate our policies: hallucinations: they often invent false information and cite non-existent references. unencyclopedic tone: they tend to be vague, promotional, or essay-like, rather than neutral and factual. copyright issues: they may closely paraphrase existing text, leading to copyright violations. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information. This draft's references do not show that the subject meets Wikipedia's criteria for inclusion. The draft requires multiple published secondary sources that: provide significant coverage: discuss the subject in detail, not just brief mentions or routine announcements; are reliable: from reputable outlets with editorial oversight; are independent: not connected to the subject, such as interviews, press releases, the subject's own website, or sponsored content. Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia. If you would like to continue working on the submission, click on the "Edit" tab at the top of the window. If you have not resolved the issues listed above, your draft will be declined again and potentially deleted. If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors. Please do not remove reviewer comments or this notice until the submission is accepted. Where to get help If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews. If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed. How to improve a draft Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia. Help:Wikitext – how to use the markup Help:Referencing for beginners – how to include references Wikipedia:Article development – how to develop your article Wikipedia:Writing better articles – how to improve your article Wikipedia:Verifiability – make sure your article includes reliable third-party sources You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Add tags to your draft Editor resources Easy tools: Citation bot (help) | Advanced: Fix bare URLs Declined by Helpful Raccoon 2 days ago. Last edited by Systemsnull 39 hours ago. Reviewer: Inform author. This draft has been resubmitted and is currently awaiting re-review.

• Comment: Please rewrite from scratch without the use of LLMs Helpful Raccoon (talk) 03:11, 3 June 2026 (UTC)

• Comment: In accordance with the Wikimedia Foundation's Terms of Use, I disclose that I have been paid by my employer for my contributions to this article. Systemsnull (talk) 23:55, 2 June 2026 (UTC)

Unity Catalog is a metadata and governance catalog for data and artificial intelligence assets, released under the Apache License. It includes a unified namespace for tables, unstructured data volumes, and functions, with APIs that can be accessed with multiple compute engines. It also manages table formats including Delta Lake and Apache Iceberg.^[1][2] The source code for the project is part of the LF AI & Data Foundation, an open source nonprofit software foundation.^[3][4] The catalog was originally developed at Databricks, which also offers it as a managed service.^[5]

Unity Catalog works by organizing data and AI assets in a hierarchical namespace consisting of catalogs, schemas, and other securable objects.^[2][6][7] It manages structured tables, supporting formats such as Delta Lake, Apache Iceberg, Apache Parquet, CSV, and JSON; and unstructured data through volumes; and machine-learning assets such as functions and models.^[2][8]

The governance features in the project include credential vending, a feature where the catalog server issues scoped credentials to clients accessing underlying cloud storage, and support for the the Apache Iceberg REST Catalog API and Apache Hive metastore API.^[2][8] By acting as a layer that exposes open APIs, implementation provides an interface for external clients, such as engines like Apache Spark to read tables, volumes, and functions that are managed by the catalog.^[9]

Unity Catalog leverages an OpenAPI-based REST specification and an reference server, with client libraries and SDKs.^[8][6] The server is compatible with the popular Apache Iceberg REST Catalog and provides compatibility with the Apache Hive metastore API.^[2][8]

• Delta Lake
• Apache Iceberg
• Data lakehouse
• Metadata management
• LF AI & Data Foundation

• Official website
• Unity Catalog on GitHub

Category:Free software Category:Data management software Category:Metadata Category:Big data products Category:Software using the Apache license Category:2024 software