Redbird AI automatically syncs operational data from MySQL into dbt transformation pipelines and writes transformed analytics back to MySQL tables. Stop manually exporting production data, running transformation scripts, and updating operational tables with aggregated metrics.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically detect new or updated MySQL tables and generate corresponding dbt staging models with proper schema definitions. Redbird monitors your production MySQL databases and keeps dbt source configurations synchronized, eliminating manual YAML updates and schema drift.
Push completed dbt model outputs from your data warehouse back into MySQL tables that power operational dashboards and applications. Redbird handles incremental updates, schema changes, and ensures your production MySQL reporting layer stays current with your analytics transformations.
Monitor dbt test results for models sourced from MySQL and automatically flag upstream data quality problems in your operational databases. Redbird correlates test failures with specific MySQL tables and columns, giving engineering teams actionable alerts about production data issues.
Pull column descriptions, foreign key relationships, and table metadata from MySQL information_schema and automatically populate dbt model documentation. Redbird keeps your dbt docs synchronized with production database schemas without manual YAML maintenance.
Automatically configure and run dbt snapshot models for critical MySQL tables that need slowly-changing dimension tracking. Redbird identifies tables with update patterns requiring historical preservation and generates snapshot model code that captures changes over time.
Convert dbt metrics and aggregate models into MySQL materialized views that applications can query directly. Redbird translates your analytics layer definitions into optimized MySQL structures, ensuring consistent metric calculations between BI tools and operational systems.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize dbt and MySQL with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird AI understands both dbt's transformation workflow semantics and MySQL's relational schema structures, enabling intelligent automation across your analytics and operational data layers.
Redbird parses dbt project files, model dependencies, and test definitions while simultaneously mapping MySQL table structures, foreign key relationships, and index configurations. It understands how your dbt staging models map to MySQL source tables, identifies schema drift automatically, and knows which transformed outputs should flow back into operational tables. The AI recognizes data type conversions between your warehouse and MySQL, handles incremental model logic, and maintains referential integrity across both systems.
faster than custom scripts to sync dbt and MySQL
Redbird can pull from dbt and MySQL simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either dbt or MySQL.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from dbt into MySQL, or from MySQL back into dbt. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start workflows from any dbt run event or MySQL schema change, then automate actions across both systems.
Trigger when any dbt model finishes running successfully or fails in your transformation pipeline.
Detect when data quality tests fail on specific models, sources, or table columns.
Trigger when source data freshness thresholds are exceeded for MySQL-sourced tables.
Automatically create new dbt staging model SQL files with proper schema and source configurations.
Modify source definitions, add table documentation, or update freshness configurations programmatically.
Trigger targeted dbt runs for specific models, tags, or dependency chains based on upstream changes.
Detect when columns are added, modified, or removed from MySQL tables used as dbt sources.
Trigger when new tables appear in monitored MySQL databases or schemas.
Alert when specific MySQL tables cross volume thresholds that may impact transformation performance.
Generate new MySQL tables with schema matching dbt model output for operational reporting.
Write dbt transformation results back to existing MySQL tables with incremental or full refresh logic.
Trigger MySQL procedures after dbt transformations complete to update application-layer data.
Redbird AI connects dbt and MySQL with your entire data ecosystem. Automate the workflows between your transformation layer and operational databases without writing integration code.