Connect Airflow and
Azure SQL with AI

Redbird AI connects your workflow orchestration platform with your managed SQL databases. Stop writing custom operators and maintenance scripts to sync pipeline metadata, trigger workflows from database events, or orchestrate Azure SQL operations from your DAGs.

No code required
Live in minutes
SOC 2 Type II

What you can automate today

Redbird gives your team ready-to-run workflows — just connect your accounts and go.

Sync Airflow DAG run metadata and task logs into Azure SQL tables

Automatically capture pipeline execution history, task durations, retry counts, and failure logs from Airflow into Azure SQL for cross-system reporting. Build unified data quality dashboards that combine pipeline health with business metrics. Enable analytics teams to query workflow performance without Airflow database access.

Trigger Airflow DAGs when new records appear in Azure SQL change tables

Monitor Azure SQL tables for new or updated records and automatically kick off Airflow workflows in response. Handle event-driven ETL scenarios where database changes need to trigger downstream processing. Replace polling-based sensors with real-time database change detection.

Archive completed Airflow task logs and XCom data to Azure SQL storage

Offload historical workflow execution data from Airflow's metadata database to Azure SQL for long-term retention. Maintain queryable archive of task outputs, variables, and inter-task communication for compliance. Keep your Airflow metadata database lean while preserving complete audit trails.

Alert teams in Azure SQL monitoring tables when Airflow pipelines fail or SLA breach

Push real-time alerts about DAG failures, task retries, or missed SLAs into Azure SQL tables that feed operational dashboards. Enable centralized incident tracking that combines pipeline failures with application errors. Route alerts based on pipeline tags, owners, or criticality levels stored in Azure SQL.

Orchestrate Azure SQL maintenance operations from scheduled Airflow workflows

Use Airflow DAGs to coordinate index rebuilds, statistics updates, and database consistency checks on Azure SQL. Schedule complex multi-step database maintenance with dependency management and retry logic. Track execution history and performance of maintenance operations alongside data pipeline runs.

Enrich Azure SQL application tables with Airflow pipeline execution context and lineage

Append workflow run IDs, execution timestamps, and data freshness indicators to records written by Airflow pipelines in Azure SQL. Enable downstream applications to understand data provenance and processing history. Surface pipeline context directly in business intelligence reports and application UIs.

Live in four steps

No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.

01

Connect your accounts

Authorize Airflow and Azure SQL with OAuth or API credentials. Redbird never stores your data — it just passes through.

02

Describe what you want

Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.

03

Review and activate

Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.

04

Let it run — and iterate

Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.

Built for data-driven teams

Redbird understands Airflow's DAG structures, task dependencies, and execution metadata alongside Azure SQL's tables, stored procedures, and T-SQL schemas — enabling intelligent automation between orchestration and operational databases.

AI that understands workflow orchestration and enterprise SQL databases

Redbird maps Airflow's task instances, DAG runs, and XCom values to Azure SQL tables, columns, and relationships without manual schema translation. Our AI recognizes temporal patterns in pipeline execution and aligns them with Azure SQL datetime fields and partitioning schemes. We handle the complexity of Airflow's nested metadata structures and Azure SQL's T-SQL-specific data types, ensuring reliable synchronization. Redbird intelligently batches operations to respect Azure SQL transaction limits while maintaining Airflow workflow integrity.

DAG run metadata mapping
T-SQL procedure orchestration
Task instance change detection
Azure SQL connection pooling
10×

faster than writing custom Airflow operators and Azure SQL connectors

No provider packages, connection hooks, or SQL templating required

Auto-generated reports

Redbird can pull from Airflow and Azure SQL simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.

Trigger-based alerts

Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Airflow or Azure SQL.

Enterprise-grade security

SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.

Bidirectional sync

Push data from Airflow into Azure SQL, or from Azure SQL back into Airflow. Resolve conflicts with configurable merge rules.

Full audit trail

Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.

Triggers & actions for every team

Start automations from any Airflow pipeline event or Azure SQL database change — Redbird handles the orchestration.

Airflow
Triggers & Actions
Trigger

DAG run completes or fails

Trigger when any Airflow DAG finishes execution with success, failure, or other terminal state.

Trigger

Task instance enters retry state

Fire when a specific task fails and enters retry mode, capturing retry count and error context.

Trigger

SLA miss detected for pipeline

Activate when DAG or task execution exceeds defined SLA thresholds in Airflow.

Action

Trigger DAG run with custom config

Programmatically start an Airflow DAG execution with specified configuration JSON and logical date.

Action

Update variable or connection

Modify Airflow variables or connection parameters that DAGs reference during execution.

Action

Clear task instances for rerun

Reset task states to allow re-execution of specific pipeline steps without full DAG rerun.

Azure SQL
Triggers & Actions
Trigger

New rows inserted into table

Detect when records are added to specific Azure SQL tables, with optional column-based filtering.

Trigger

Stored procedure execution completes

Fire when designated T-SQL stored procedure finishes, capturing output parameters and return codes.

Trigger

Table row count threshold crossed

Trigger when a monitored Azure SQL table exceeds or falls below configured row count limits.

Action

Execute parameterized SQL query

Run T-SQL statements with dynamic parameters, supporting inserts, updates, and complex joins.

Action

Bulk insert records into table

Efficiently write large datasets to Azure SQL tables with automatic batching and transaction management.

Action

Call stored procedure with arguments

Invoke Azure SQL stored procedures with input parameters and capture output values and result sets.

Airflow
+
Azure SQL

Ready to connect your stack?

Sync Airflow pipeline metadata with Azure SQL databases, trigger workflows from database events, and orchestrate SQL operations — all without custom operators or maintenance overhead.

Get started → Book a demo