Data build tool
| dbt | |
|---|---|
| Developer | dbt Labs |
| Initial release | December 3, 2021; 3 years ago (2021年12月03日) |
| Stable release | |
| Repository | |
| Written in | Python |
| Operating system | Microsoft Windows, macOS, Linux |
| Available in | Python |
| Type | Data analytics, data management |
| License | Apache License 2.0 |
| Website | docs |
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Data build tool (dbt) is an open-source command line tool that helps analysts and engineers transform data in their warehouse more effectively.[2]
History
[edit ]It started at RJMetrics in 2016 as a solution to add basic transformation capabilities to Stitch (acquired by Talend in 2018).[3] The earliest versions of dbt allowed analysts to contribute to the data transformation process following the best practices of software engineering.[4]
From the beginning, dbt was open source.[5] In 2018, the dbt Labs team (then called Fishtown Analytics) released a commercial product on top of dbt Core.[6]
Funding
[edit ]In April 2020, dbt Labs announced its Series A led by Andreessen Horowitz.[7] In November, dbt Labs announced its Series B led by Andreessen Horowitz and Sequoia.[8] And in June 2021, dbt Labs raised its Series C led by Altimeter, Sequoia, and Andreessen Horowitz.[9] In February 2022, the company raised 222ドル million for its Series D, at a 4ドル.2 billion valuation.[10]
Overview
[edit ]Dbt enables analytics engineers to transform data in their warehouses by writing select statements, and turns these select statements into tables and views. Dbt does the transformation (T) in extract, load, transform (ELT) processes – it does not extract or load data, but is designed to be performant at transforming data already inside of a warehouse. Dbt has the goal of allowing analysts to work more like software engineers, in line with the dbt viewpoint.[11]
Dbt uses YAML files to declare properties. seed is a type of reference table used in dbt for static or infrequently changed data, like for example country codes or lookup tables), which are CSV based and typically stored in a seeds folder.
References
[edit ]- ^ "Release dbt-core v1.10.11 · dbt-labs/dbt-core". GitHub. Retrieved 9 September 2025.
- ^ Atwal, Harvinder (9 December 2019). Practical DataOps: Delivering Agile Data Science at Scale. Apress. p. 223. ISBN 978-1-4842-5104-1.
- ^ "Stitch is joining Talend". Stitch Data. 2018年11月07日. Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.
- ^ "Goodbye RJMetrics, Hello Fishtown Analytics". dbt Blog. 2016年08月01日. Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.
- ^ Cai, Kenrick. "Dbt Labs In Talks To Raise At 6ドル Billion Valuation, Six Months After Becoming A Unicorn". Forbes. Retrieved 2023年04月01日.
- ^ "Sinter Release Notes, August 2018: pull request builder, fine-grained GitHub permissions, and more". 2018年07月31日. Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.
- ^ "Fishtown Analytics raises 12ドル.9M Series A for its open-source analytics engineering tool". TechCrunch. 2020年04月22日. Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.
- ^ "Fishtown Analytics raises 29ドル.5M Series B for its data engineering platform". TechCrunch. 2020年11月11日. Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.
- ^ "Of the Community, By the Community, For the Community". dbt Blog. 2021年06月30日. Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.
- ^ Cai, Kenrick (24 Feb 2022). "VENTURE CAPITAL Dbt Labs Raises At 4ドル.2 Billion Valuation, 2ドル Billion Less Than First Planned". Forbes. Forbes. Archived from the original on 11 May 2022. Retrieved 11 May 2022.
The Philadelphia-based data analytics startup revealed Thursday that it had settled on a 4ドル.2 billion valuation as part of a 222ドル million Series D funding round
- ^ "dbt viewpoint". Archived from the original on 2021年11月07日. Retrieved 2021年11月07日.