MatrixOne Git4Data Tutorial

Runnable companion code for the MatrixOne Git4Data Deep Dive article series — Git-style version control for data at scale (commit, branch, diff, merge, cherry-pick, time travel), built into MatrixOne.

What is Git4Data? If you treat a database as a Git repository and a table as a file in it, MatrixOne lets you run everyday Git operations — snapshot, clone, branch, diff, merge, cherry-pick, restore — over terabytes of data, almost instantly. It's the same workflow software engineers use on code, now on data.

The series

Part	Theme	Topic	Article	Code
1	Concept	The Git moment for data at scale	Blog ↗	—
2	Concept	Hands on: every Git primitive, from zero	Blog ↗	02-hands-on/
3	Concept	Under the hood: why snapshot/diff/merge are this fast	Blog ↗	—
4	Concept	The data-versioning landscape: git4data vs lakeFS / Dolt / Snowflake	Blog ↗	—
5	Data Ops	Incident rescue: snapshot / DIFF investigation / PITR	Article	05-incident-rescue/
6	Data Ops	Collaborative development: one branch per engineer	Article	06-collaborative-dev/
7	Data Ops	Write-Audit-Publish: a release gate for data	Article	07-write-audit-publish/
8	AI Training	ML continuous learning: train only the delta	Article	08-ml-incremental/
9	AI Training	SFT curation: clean in place, with receipts	Article	09-sft-curation/
10	AI Training	Collaborative labeling: disagreement IS the conflict	Article	10-labeling-collab/
11	AI Training	RLHF preference data: consensus, re-judging, reproducibility	Article	11-rlhf-preference/
12	AI Training	Multimodal × lakeFS: bytes there, catalog here	Article	12-multimodal-lakefs/
13	Agents	Agent memory: versioned, branchable, rewindable	Article	13-agent-memory/
14	Agents	Agent traces: queryable, joinable, versioned	Article	14-agent-trace/
15	Agents	Agent self-evolution (finale): branch / evaluate / merge / roll back	Article	15-agent-evolution/

Concept parts (1–4) link out to the published blog. Each practice part (5–15) ships its full article in-folder — article_en.md / article_zh.md — right next to the runnable SQL.

Quick start (5 minutes)

# 1. Run a local MatrixOne (open source, MySQL-compatible)
docker run -d -p 6001:6001 --name matrixone matrixorigin/matrixone:4.0.0-rc3

# 2. Run the Part 2 walkthrough — every Git primitive on 1,000,000 rows
mysql -h 127.0.0.1 -P 6001 -u root -p111 < 02-hands-on/git4data_primitives.sql

Default credentials: user root, password 111, port 6001.

What Part 2 covers

02-hands-on/git4data_primitives.sql is a single, copy-paste-runnable script (English comments) that walks through:

• commit / tag / reset — CREATE SNAPSHOT, time-travel SELECT … {snapshot=…}, RESTORE
• clone — zero-copy CREATE TABLE … CLONE
• branch — lineage-tracked DATA BRANCH CREATE
• diff — row-level DATA BRANCH DIFF … OUTPUT SUMMARY / COUNT / LIMIT / FILE
• merge — three-way DATA BRANCH MERGE … WHEN CONFLICT FAIL | SKIP | ACCEPT
• cherry-pick — DATA BRANCH PICK … KEYS(…)
• point-in-time recovery — CREATE PITR + RESTORE … FROM PITR "…"
• granularity — the same semantics at table / database / account / cluster levels
• scale — measured numbers showing snapshot/clone/branch cost is independent of table size

It loads a million rows with a single generate_series statement (no external files needed) and cleans up after itself.

Measured: cost is independent of data size

Same table, same operations, on a single-node Docker MatrixOne (diff/merge each touch only 1,000 rows):

Steady-state, median of several runs (MatrixOne 4.0.0-rc3):

table size	load	CREATE SNAPSHOT	CLONE	DATA BRANCH CREATE	DIFF (1000)	MERGE (1000)
1,000,000	0.5 s	6 ms	6 ms	7 ms	13 ms	64 ms
10,000,000	5.3 s	8 ms	8 ms	7 ms	21 ms	178 ms
100,000,000	41 s	5 ms	25 ms	19 ms	23 ms	189 ms

Snapshot is dead constant (it just names a metadata directory). Clone/branch copy the metadata directory, not the data — 100× the data, clone rises only 6 ms → 25 ms. Diff/merge scale with how many rows changed, not table size. (The first snapshot of a freshly loaded table is ~10–12 ms — a one-time flush of in-memory data — then drops to the steady-state numbers above.)

Links

• MatrixOne: https://github.com/matrixorigin/matrixone
• Docs: https://docs.matrixorigin.cn/

License

Apache 2.0