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datafold
data-diff
Python2022–2025
datafold / data-diff · Archived

data-diff

Compare tables within or across databases

8Distinct people
10Mentions
0Explicit recommenders
3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Compare tables within or across databases

GitHub

Where it is used

No documented product use has been verified yet.

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

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 6:01:08 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 year10 dated mentions

Observed mentions: 2022-06-22 15:28:04 UTC to 2025-02-19 00:43:27 UTC.

02462022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 6 mentions; 4 submissions, 2 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

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
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC642
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC202
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

1 sources
As a data engineer, who is regularly fighting - "these two databases have different SQL dialects" - "did we miss a few rows due to poor transaction-isolation when trying to query recently changed rows on the upstream database" - "is there some checksum of a region of cells that accepts any arrangement of rows and columns that doesn't require me to think about ordering?" - "is there a subtle data format conversion problem silently mangling my data?" ...I've toying with trying to find a way to serialize everything consistently into something that can be XOR'd, then compare the output of XOR for two tables in two different databases that should be identical, without having to do some giant order-by comparison. Ideally, if necessary, this could be done by eye with two query windows pointing at two different databases... Basically, Datafold's
Read the rest
datadiff, but in a way that could plausibly be home-rolled for on-premise applications (especially quick spot-checks), and not be a total maintenance nightmare... https://github.com/datafold/data-diff Don't have anything working yet, but it just seems like one could at least xor a bunch of integers and get something useful... Somehow.
In XOR

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