Automate multi-step database workflows without backend code

Chain queries and pass results between steps

Most real database tasks aren't a single query—they're a sequence. Look up a user, check their status, update a record, log the result. Silent Dock Workflows let you define each step as a query and automatically pass the output of one step into the next using context variables ($ctx.varName). No intermediary scripts, no glue code.

• Query steps with result variables saved to context
• Use $ctx.result.rows.0.id in subsequent queries
• Supports MySQL, PostgreSQL, and MongoDB

Add conditional logic without writing code

Condition steps let you branch based on query results. Compare a context value against a threshold, check whether a result is null, or evaluate row counts—then route execution down the correct path. All comparisons are structural (no eval), so your pipelines stay safe even with team access.

• Operators: eq, neq, gt, gte, lt, lte, contains, is_null, is_not_null
• onTrue / onFalse routing to any step in the workflow
• No code evaluation — safe for shared environments

Transform query results in place

Transform steps let you reshape data between queries without leaving the workflow. Extract a list of IDs with pluck, sum a numeric field, grab the first row, or join IDs into a comma-separated string for an IN (...) clause. Built-in operations keep transformations safe and auditable.

• count — count rows or items
• first — take the first result
• pluck — extract a field from every row
• sum — sum a numeric field across rows
• join_ids — format IDs for SQL IN clauses

Reuse existing Actions as workflow steps

Already have parameterized Actions defined for your database? Call them directly from a workflow step. Map context values to action parameters so your existing, tested logic becomes a reusable building block in larger pipelines.

• Call any existing Action from a workflow
• Map $ctx.varName or literal values to action parameters
• Compose complex pipelines from simple, tested building blocks

Full execution log for every run

Every workflow execution is logged step-by-step: which steps ran, how long each took, what was returned, and any errors. You can review the full history of every pipeline run directly in the dashboard—useful for debugging, compliance, and auditing automated operations.

• Per-step status, duration, and result snapshot
• Configurable error handling: stop on failure or continue
• Full execution history accessible from the dashboard

Who uses database workflow automation?

Workflows are built for developers and power users who need to automate multi-step database operations but don't want to write, host, or maintain a backend service for every automation task. Common use cases include:

• User provisioning pipelines (create record → send welcome → log event)
• Data migration sequences with conditional logic
• Scheduled cleanup jobs (query stale records → conditionally archive → delete)
• Multi-step order or transaction processing
• Automated reporting pipelines that aggregate and write summary data