dolt
Dolt, Git for Data
Runssource: GitHubhomepageGoApache-2.0commit 4a2e8ce2f155
Go, Apache-2.0 licensed. The project labels itself: agent memory, agent memory server, ai agents, ai database, data version control, data versioning, database and database version control.
dolt runs. An Argusic agent installed it in 16 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Dolt v2.3.5 binary runs as a CLI tool and MySQL-compatible SQL server; version control operations (init, add, commit, branch, merge, log) work via both CLI and SQL procedures; bats integration tests pass on core functionality
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 100 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- Source build failed: missing system libraries unicode/uregex.h (libicu-dev) and gozstd CGo bindings2 minutes
- ./sql.bats: 6 of 118 tests fail (tests #2, #18, #19, #20, #21, #23, #102, #110)
- Install time
- 16 minutes
- Cold machine to finish
- 28 minutes
- Errors hit and fixed
- 2 hit, 2 fixed with no human help
- How the result was proved
- dolt version returned 'dolt version 2.3.5'; init.bats (20/20), sql.bats (112/118), commit.bats (14/14), branch.bats (35/35), merge.bats (48/48), add.bats (2/2) all passed; pymysql connected to dolt sql-server on 127.0.0.1:3307 with SELECT 1 and returned server version '8.0.31'; full Git-like workflow exercised (init, create table, insert, commit, branch, checkout, merge, log)
- Model tokens used
- 369,308
- Exact commit tested
- 4a2e8ce2f155
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
exec /bin/sh -lc 'export PATH="$HOME/bin:$PATH" && dolt sql -q "SELECT COUNT(*) FROM employees;" 2>&1' i… succeeded in 0ms: +----------+ | COUNT(*) | +----------+ | 4 | +----------+ Now I have all the data needed. Here's my final report. tokens used 369,308 Now I have all the data needed. Here's my final report.
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Installed in 16 minutes, faster than the median of the 3 comparable projects Argusic has measured.
- Recovered from all 2 errors without a human stepping in, which says the failures are documented well enough to solve.
- Ran without a GPU, so it does not need one to start.
- Licensed Apache-2.0, as reported by its host.
What did not, or is not known
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 4 agent-memory projects Argusic has installed and timed, dolt was the 2nd fastest to reach a running state, and 4 of 4 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
Topics (from GitHub)
agent-memoryagent-memory-serverai-agentsai-databasedata-version-controldata-versioningdatabasedatabase-version-controldatabase-versioningdecentralized-databasegitgit-databasegit-for-datagit-for-databasesgit-sqlimmutable-databasemariadbmysqlsqlversion-controlled-database
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/dolt)Questions
- Does dolt run?
- Yes. dolt runs. Argusic installed and launched it on a clean machine in 16 minutes, hitting 2 errors on the way, and recorded the session.
- How did Argusic test dolt?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4a2e8ce2f155. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test dolt?
- The run that produced this verdict cost $0.11: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does dolt take to install?
- 16 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does dolt need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing dolt?
- 2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does dolt compare with the alternatives?
- Of the 4 agent-memory projects Argusic has installed and timed, dolt was the 2nd fastest to reach a running state, and 4 of 4 reached one at all.
- Where is the evidence for dolt?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.