SaturnSQL
SQL editor for data teams
SaturnSQL is a collaborative SQL editor for teams. Connect PostgreSQL, MySQL, MariaDB, SQL Server, Oracle, BigQuery, Redshift, ClickHouse or DynamoDB, then write, share and organize queries in one browser workspace instead of everyone running their own client with their own credentials. Any saved query can run on a schedule and deliver results straight to Google Sheets or Slack, so recurring reports stop being a manual export.
Features
- Shared workspace: one set of connections and a shared query library for the whole team.
- Smart editor: schema-aware autocomplete, AI SQL help, saved queries in folders.
- Scheduled delivery: run any saved query on a cron, results land in Google Sheets or Slack.
- Dashboards and charts: turn query results into tiles without adding a BI tool.
Use Cases
- Give analysts and ops read access to production data without handing out credentials.
- Move off PopSQL or SeekWell, keeping the shared query library and scheduled reports.
- Send recurring reports to Sheets or Slack instead of exporting CSVs by hand.
- Ad hoc analysis and on-call debugging against live data.
- Self-service numbers for non-SQL teammates through shared queries and dashboards.
Comments
Scheduled delivery to Google Sheets or Slack is a practical bridge between an SQL workspace and the people who consume recurring reports. The shared connection model could simplify handoffs, but I’d want per-query parameter support so one saved query can serve different teams or date ranges without duplicating it. How do you handle long-running jobs or schema changes when a scheduled delivery fails?
Shared connections plus scheduled Slack and Sheets delivery solve real ops friction. For production use, the deciding features would be role-based permissions at the connection and query level, query audit logs, and enforceable read-only access. Surfacing those clearly in onboarding would make a team's security review much easier.
As a dev-tool builder, the collaborative angle here stands out — most SQL editors are great for individuals but fall apart for teams. Shared connections plus a shared query library directly addresses the 'tribal knowledge in everyone's head' problem. The scheduled delivery to Sheets/Slack is the feature that would have sold my team — it replaces a surprising amount of manual export-and-email. Curious whether you support query parameters or variables in scheduled runs. Congrats on the launch!
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Comments
Scheduled delivery to Google Sheets or Slack is a practical bridge between an SQL workspace and the people who consume recurring reports. The shared connection model could simplify handoffs, but I’d want per-query parameter support so one saved query can serve different teams or date ranges without duplicating it. How do you handle long-running jobs or schema changes when a scheduled delivery fails?
Shared connections plus scheduled Slack and Sheets delivery solve real ops friction. For production use, the deciding features would be role-based permissions at the connection and query level, query audit logs, and enforceable read-only access. Surfacing those clearly in onboarding would make a team's security review much easier.
As a dev-tool builder, the collaborative angle here stands out — most SQL editors are great for individuals but fall apart for teams. Shared connections plus a shared query library directly addresses the 'tribal knowledge in everyone's head' problem. The scheduled delivery to Sheets/Slack is the feature that would have sold my team — it replaces a surprising amount of manual export-and-email. Curious whether you support query parameters or variables in scheduled runs. Congrats on the launch!
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