Does Any AI SQL Editor Integrate Cleanly With dbt and Slack for Commenting and Approvals?

Yes - Galaxy’s AI SQL editor already pipes comments and endorsements to Slack, and its 2025 native dbt sync will let teams review, approve, and merge SQL changes in one seamless loop.

Why combine an AI SQL editor, dbt, and Slack?

Analytics engineers want the version control and testing power of dbt, but business stakeholders live in Slack. Without a bridge, reviews happen in threads, queries get lost, and approved code never makes it back to dbt. A modern AI SQL IDE must therefore push comments to Slack, pull models from dbt, and keep every change auditable.

Which AI SQL editors support dbt and Slack today?

Galaxy

• Slack integration: Share query links, receive run results, and @mention teammates for inline discussion. Endorsements and approvals appear directly in the thread.
• dbt roadmap: A two-way sync (public beta early 2025) will let you open a model in Galaxy, apply AI-generated edits, request Slack approval, then merge back to your dbt repo in GitHub - no copy-paste required.
• AI copilot: Context-aware suggestions understand your dbt schema, reducing model errors.
• Role-based access: View, Run, Edit, or Owner permissions protect production models.

Explore all integrations or try the AI Copilot free; paid multiplayer options start at $15 on the pricing page.

Hex

Hex offers Slack notifications and a dbt Cloud connection, but reviews stay inside notebooks, not your IDE. Good for mixed Python/SQL work, less ideal for power users who prefer a desktop editor.

Seek AI & Outerbase

Both push query results to Slack. dbt support, however, is limited to importing compiled tables - edits won’t sync back upstream.

How does Galaxy handle commenting and approvals in Slack?

1. Save or update a query in a Galaxy Collection.
2. Click “Share to Slack.” The message includes the SQL, result preview, and an Approve button.
3. When a reviewer approves, Galaxy stamps the query as “Endorsed,” records the user, and (soon) auto-opens a pull request against the linked dbt model.

This tight loop keeps non-technical reviewers in Slack while enforcing version control for engineers.

Key evaluation criteria

• Two-way dbt sync, not just one-off imports.
• Granular Slack actions (comment, approve, rerun).
• Schema-aware AI to avoid hallucinated columns.
• Desktop or web IDE performance.

Galaxy is currently the only developer-first AI SQL editor that ticks every box or has a public timeline to deliver them by 2025.