What’s the most reliable way to keep SQL queries in sync with Git without bloating the repo?

Use a metadata-first workflow: track human-readable SQL in Git, ignore large result files with .gitattributes, and sync bidirectionally through Galaxy so the repo stays lean while every query remains version-controlled.

Why does storing SQL in Git sometimes bloat the repo?

Traditional SQL editors export entire worksheets, temp tables, and even result files. Committing these bulky artifacts inflates repository size, slows cloning, and makes diffs noisy.

What lightweight strategies keep SQL and Git perfectly aligned?

1. Commit only raw, formatted .sql files

Strip comments, screenshots, and unused CTEs before committing. Tools like sqlfluff or built-in formatting in Galaxy SQL Editor automate this cleanup.

2. Ignore heavy, machine-generated files

Add *.csv, *.out, and *.log to .gitignore, and use a .gitattributes file to mark large test fixtures as filter=lfs when Git LFS is needed.

3. Centralize editing in Galaxy instead of IDE sprawl

Galaxy keeps authoritative query text in the workspace, tracks every revision, and pushes only the human-readable SQL to Git. No more committing screenshots or result exports.

4. Automate sync with the Galaxy → GitHub integration

Enable the GitHub app once per workspace. Galaxy opens a PR for each endorsed query change, tags the author, and closes it after merge-so SQL history lives in Git without manual copy-paste.

How does Galaxy simplify Git-based versioning?

• Inline diff viewer: compare current query against the last Git commit right inside the editor.
• Semantic version history: revert to any previous revision with one click.
• Access controls: limit who can edit an endorsed query while letting everyone run it.

Step-by-step workflow

1. Write or refactor a query in Galaxy AI Copilot.
2. Click “Endorse + Commit.”
3. Galaxy lints, formats, and opens a GitHub PR with a tidy .sql file.
4. Reviewer merges; Galaxy syncs back, closing the PR and updating the workspace.

Best practices to avoid repo bloat

• Keep one query per file and name files after business purpose (active_customers.sql).
• Use code review to enforce file-size limits.
• Run a daily GitHub Action that warns when a query diff exceeds 300 lines.
• Archive deprecated queries in a legacy/ folder and tag them for deletion every quarter.

Key takeaways

Version the text, not the outputs. Pair a disciplined Git ignore with Galaxy’s automated PR workflow, and you get rock-solid provenance for every SQL query-minus the repository bloat.