Draft:ChDB

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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. 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 months ago. Last edited by Citation bot 2 months ago. This draft has been resubmitted and is currently awaiting re-review.

• Comment: Please rewrite from scratch without the use of LLMs. Corporate blogs are not reliable sources. Helpful Raccoon (talk) 23:23, 3 June 2026 (UTC)

chDB is an open-source embedded SQL engine for online analytical processing (OLAP), based on ClickHouse. It runs the ClickHouse query engine in-process, inside a host application, rather than through a separate database server, and is distributed mainly as a Python package under the Apache License 2.0.^[1][2] In addition to Python, the project provides bindings for C, C++, Go, JavaScript, Bun, and Rust.^[3]

chDB was created by Auxten Wang and first published as a Python package in 2023, with version 1.0.0 following in December of that year.^[4][5][6] It was acquired by ClickHouse, Inc. in March 2024.^[4][2]

Because the ClickHouse engine runs in the same process as the calling application, data moves between them without being copied, so a query can read values already held in memory, such as a pandas DataFrame in a Jupyter notebook, and return its results into the same session.^[1]

chDB uses the same SQL as ClickHouse and can read the formats ClickHouse supports, more than 70 in total, among them Parquet, CSV, and JSON.^[7][8][9] A single query can combine these with in-memory data and remote sources without loading them into a server first, and a session can keep data between queries for multi-step work.^[9] Its Python API works directly with dataframes, which makes it convenient to call from existing data-science code.^[10]

Like DuckDB, chDB is an embedded OLAP database, and the two are often compared for local analytics.^[11][12] It is mainly an option for developers already working with ClickHouse, especially when a workload relies on ClickHouse-specific SQL features such as array functions.^[11][12]