Redbird AI syncs Airflow pipeline metadata with PostgreSQL and orchestrates database operations based on DAG events. Stop writing custom operators and manually tracking pipeline runs in spreadsheets—automate the connection between your workflow orchestration and your operational database.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Capture every Airflow DAG execution—runtime, status, task-level failures, retry counts—and write structured records to PostgreSQL. Build operational dashboards that query live pipeline history without hitting the Airflow metadata database. Surface trends like task duration increases or failure patterns across environments.
Start data transformation pipelines automatically when source tables in PostgreSQL are updated or reach row count thresholds. Eliminate cron-based polling—let database events drive orchestration. Ideal for CDC workflows where downstream processing must kick off immediately after upstream inserts.
Move Airflow task logs, XCom outputs, and execution context to long-term PostgreSQL storage on a schedule. Reduce metadata database bloat while maintaining audit trails. Query historical execution artifacts alongside application data for compliance reporting and forensic analysis.
Pull configuration data, feature flags, or lookup tables from PostgreSQL and inject them as Airflow variables or connections. Update pipeline behavior without redeploying DAGs—let database-driven config control orchestration logic. Support multi-tenant pipelines that read tenant-specific settings from Postgres.
When DAG tasks fail, query PostgreSQL for related context—affected customer IDs, transaction counts, or system state—and include it in alerts. Give on-call engineers the full picture without manual lookups. Automatically create incident records in Postgres linking failures to impacted business entities.
Combine Airflow DAG metrics with application-level PostgreSQL data—records processed, rows updated, business KPIs affected by each pipeline run. Create unified reports showing both orchestration health and business impact. Surface SLA breaches alongside the data quality issues they cause.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Airflow and PostgreSQL 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 structure, task dependencies, and execution metadata alongside PostgreSQL's schemas, constraints, and query patterns—no boilerplate operators required.
Redbird parses Airflow DAG definitions to understand task lineage, dependencies, and execution context. It simultaneously maps PostgreSQL table structures, foreign keys, indexes, and data types. When you connect them, Redbird automatically determines how to serialize DAG metadata into relational tables or how to translate database triggers into DAG runs—without writing custom PythonOperators or hooks. Update schemas on either side and Redbird adapts the sync logic.
faster than building custom PostgresOperator workflows and maintaining connection logic
Redbird can pull from Airflow and PostgreSQL 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 PostgreSQL.
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 PostgreSQL, or from PostgreSQL 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 workflows from DAG state changes in Airflow or table events in PostgreSQL—Redbird handles the orchestration.
Trigger when any DAG finishes execution with success, failure, or retry status.
Fire when a specific task exhausts retry attempts and enters failed state.
Detect when pipeline runtime crosses configured threshold for performance monitoring.
Programmatically start a DAG execution and pass JSON configuration parameters.
Set or modify Airflow variables used for dynamic DAG configuration.
Programmatically enable or disable DAG scheduling based on external conditions.
Trigger when new records appear in specified PostgreSQL tables or views.
Fire when a table grows beyond a configured size for batch processing triggers.
Detect when a saved SQL query returns different results indicating state changes.
Write DAG execution records, task status, or XCom data into PostgreSQL tables.
Run SQL statements with dynamic values from Airflow task context or XCom.
Merge Airflow metadata into PostgreSQL using conflict resolution for idempotent loads.
Stop maintaining custom Airflow operators and PostgreSQL hooks. Let Redbird automate the connection between your orchestration layer and operational database—so your data team can focus on pipelines, not plumbing.