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Factual
drake
Clojure2013–2026
Factual / drake

drake

Data workflow tool, like a "Make for data"

Automation & Workflows
Explore on GitHubRead Hacker News discussions
14Distinct people
21Mentions
1Explicit recommenders
1.5KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Data workflow tool, like a "Make for data"

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

Amen right back at ya! (I love the O'Reilly book cover.) I highly recommend people read your blog post. And there's also this classic:…

edw used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 4:00:59 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year21 dated mentions

Observed mentions: 2013-01-24 22:09:56 UTC to 2026-09-09 11:14:41 UTC.

024682013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC808
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC101
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC413
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC202
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC303
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC101

What Hacker News says

3 sources
rockmeamedee·Jul 11, 2018
Make is often brought out for data, "single machine ETL" jobs, but for big, complicated (and iterative) workflows it doesn't feel good enough to me. What do you folks use? Drake, "make for data" https://github.com/Factual/drake seems ok, but doesn't have "batch" jobs, (aka "pattern rules") where you can do every file in a directory matching a pattern. Others have come up with different swiss army knives but nothing ever sticks for me, it usually ends up as a single Makefile with eg 3 targets that call a bunch of shell scripts. The whole thing would be configurable to build from scratch, but not well set up to do incremental ETL on a per file basis, after I eg delete some extraneous rows in one file, clean up a column, redownload a folder, or add files to a dataset.
In How ProPublica Illinois Uses GNU Make to Load Data
fnl·Jan 27, 2018
Given the number of tools around, and as this book promotes Drake, has anyone got "comparative experience" with some of the following tools: Cookiecutter: https://drivendata.github.io/cookiecutter-data-science DataVersionControl: https://dataversioncontrol.com/ Drake: https://github.com/Factual/drake Luigi: https://github.com/spotify/luigi Pachyderm: http://www.pachyderm.io/ Sacred: https://github.com/IDSIA/sacred They all focus in slightly different ways on the issue of managing data science/machine learning workflows, so I wonder if someone has a clear preference for one of those over any another. EDIT: added Luigi
In Data Science at the Command Line

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