Automate the flow between your orchestration layer and operational database. Stop manually tracking pipeline metadata, writing custom MySQL operators, or building one-off scripts to sync job states and execution logs into your transactional systems.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically capture pipeline execution history, task durations, and failure states from Airflow and write them to MySQL audit tables. Keep operational records of every run without custom logging code. Enable real-time dashboards and historical analysis of pipeline health.
Monitor MySQL tables for data volume changes and automatically kick off downstream Airflow pipelines when new records arrive. Eliminate polling scripts and build event-driven architectures. Ensure transformation jobs run exactly when source data is ready.
Persist detailed execution logs, variable states, and inter-task communication from Airflow into structured MySQL tables. Meet audit requirements without bloating your Airflow metadata database. Query historical context across pipeline runs with standard SQL.
Surface Airflow task failures and SLA breaches directly in operational MySQL-backed applications and internal tools. Unify monitoring across your stack without requiring access to the Airflow UI. Enable support teams to track data issues alongside application incidents.
Store pipeline parameters, schedules, and connection details in MySQL and automatically create or update Airflow DAGs based on database-driven configs. Enable non-technical users to manage data workflows through familiar database interfaces. Version control pipeline logic alongside application schemas.
Append Airflow execution context—run IDs, task names, processing times—directly into MySQL application tables as they're transformed. Track which pipeline version touched each record without separate audit systems. Debug data quality issues by tracing records back to specific DAG runs.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Airflow 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 understands Airflow's DAG structures, task dependencies, and metadata schemas alongside MySQL's relational tables, indexes, and transactional patterns—bridging orchestration and operational data seamlessly.
Redbird automatically maps Airflow's task instances, DAG runs, and XCom values to your MySQL table structures without manual operator development. It understands foreign key relationships in your operational database and how they relate to pipeline execution context. The platform intelligently handles Airflow's datetime formats, state enums, and JSON fields alongside MySQL's data types and constraints. When schemas evolve in either system, Redbird adapts mappings without breaking your automation.
faster than building custom Airflow MySQL operators
Redbird can pull from Airflow 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 Airflow 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 Airflow into MySQL, or from MySQL back into Airflow. 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 automations from DAG state changes in Airflow or data events in MySQL—then take action across your entire stack.
Fire when any Airflow DAG finishes execution, whether successful, failed, or upstream_failed state.
Trigger when an Airflow task enters retry state after an initial failure.
Activate when a DAG or task misses its defined service level agreement threshold.
Programmatically start an Airflow DAG run with specific config JSON and execution date.
Manually set task state in Airflow to unblock downstream dependencies or reset failures.
Dynamically enable or disable DAG scheduling in Airflow based on external conditions.
Detect when new records appear or existing rows change in any MySQL table.
Monitor a SQL query and trigger when result set crosses a specified row count.
Fire when columns are added, removed, or altered in a MySQL table structure.
Write new records or update existing ones in MySQL tables with conflict resolution.
Run custom SELECT, UPDATE, or DELETE statements with dynamic values from upstream data.
Optimize MySQL query performance by adding indexes based on workload patterns.
Sync Airflow orchestration with MySQL operational data in minutes. Let Redbird handle the connection logic, state management, and schema mapping so your team can focus on building pipelines that matter.