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dolthub
dolt
Go2019–2026
dolthub / dolt

dolt

Dolt – Git for Data

42Distinct people
76Mentions
0Explicit recommenders
24.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Dolt – Git for Data

GitHub

Where it is used

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

What people are saying

No recommendation phrase was found in the indexed comments.

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

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 10:56:20 AM 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 year76 dated mentions

Observed mentions: 2019-08-06 22:43:54 UTC to 2026-04-14 23:55:55 UTC.

051015202019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 6 mentions; 2 submissions, 4 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 19 mentions; 2 submissions, 17 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 14 mentions; 4 submissions, 10 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 7 mentions; 2 submissions, 5 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 12 mentions; 0 submissions, 12 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 12 mentions; 2 submissions, 10 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 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
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC624
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC19217
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC14410
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC725
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC12012
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC12210
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC303
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC312

What Hacker News says

6 sources
We built a Git-style version controlled SQL database called Dolt (https://github.com/liquidata-inc/dolt) mentioned deep in this thread. It allows diffs and merges across schema and data based on commits. We are focused on the data distribution/open data use case (https://www.liquidata.co/blog/2019-10-09-where-is-the-data-c..., https://www.liquidata.co/blog/2019-12-06-the-history-of-data...) but I think a number of use cases mentioned in this thread are covered by Dolt. You do have to move a copy of your data to Dolt, it does not sit on top or beside of your current database. So, it is an extra step in your data modification workflow, similar to versioning code. You had to add a version control step into your code modification workflow.
In Show HN: Version Control for Databases
Congratulations to the Quilt team on the launch! Quilt reached out to me and suggested I chime in suggesting that people interested in versioning data also check out Dolt (https://github.com/liquidata-inc/dolt) and DoltHub (https://www.dolthub.com). We've taken the Git and GitHub for data analogy a lot more literally than Quilt has :-) We are a SQL database with native Git semantics. Instead of versioning files like Git, we version table rows. This allows for diff and conflict detection down to the cell level. We are built on top of another open source project called Noms (https://github.com/attic-labs/noms). We think there is a ton of room in this space for a bunch of tools: Quilt, Noms, QRI (https://qri.io/), Pachyderm (https://www.pachyderm.io/), and even Git. We're excited to see so many bright minds trying to solve this problem. We'r
Read the rest
e going to be populating DoltHub with a bunch of datasets we harvest from the open data community to show off the capabilities of Dolt. The coolest one so far is the Google open images dataset: https://www.dolthub.com/repositories/Liquidata/open-images.
In Launch HN: Quilt (YC W16) – A versioned data portal for S3
Sirix sounds like a very interesting system! Is it similar in its internal structure to noms (https://github.com/attic-labs/noms) or Dolt (https://github.com/liquidata-inc/dolt)? I think S3 is a good match for storing database pages as long as they are immutable. The Vectorized query processing model seems to fit this approach very well (e.g., http://oai.cwi.nl/oai/asset/14075/14075B.pdf) Anyone out there from Snowflake care to answer how Snowflake stores database pages in AWS? I haven't used BookKeeper or Pulsar myself so I can't comment on how well they might work for distributing an intent log.
In Launch HN: Quilt (YC W16) – A versioned data portal for S3
timsehn·Aug 28, 2019Submission

DoltHub. Public Launch

On August 6, we launched Dolt - Git for data open source (https://github.com/liquidata-inc/dolt). Today we publicly launched DoltHub (https://www.dolthub.com), a place on the internet to share Dolt repositories. Dolt is a SQL database that natively supports Git semantics like commits, branches, and merges. It uses a custom engine that versions table rows not files so diffs and merges are fast. The structural sharing of rows across versions allows Dolt to scale to large table sizes. DoltHub is to Dolt as GitHub is to Git. The data community can post and collaborate on open databases much as the open source community collaborates on open source. Over the next few months we're going to work really hard to publish open, maintained, and updated data on DoltHub that you can't easily get anywhere else on the internet. Think every LinkedIn resume
Read the rest
on CommonCrawl. Between now and then, we'd love it if people signed up for DoltHub and helped us seed the open data ground. We're hoping the HackerNews community enjoys what we've built :-)
13 points · Open discussion

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