Automate the pipeline between your operational database and lakehouse platform. Stop manually extracting tables, writing glue scripts, and reconciling schema changes between Azure SQL and Databricks—Redbird handles incremental sync, transformation orchestration, and bi-directional data flows automatically.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically detect changes in Azure SQL operational tables and sync them to Delta tables in Databricks. Redbird handles incremental loads using change tracking or timestamps, manages schema drift, and orchestrates upserts without custom ETL code.
Monitor row counts, data volumes, or specific business metrics in Azure SQL tables. When thresholds are crossed, automatically kick off Databricks notebooks or workflows to process the new data, train models, or generate aggregations.
After model inference or feature engineering in Databricks, automatically push scored records, predictions, or derived features back to Azure SQL tables. Keep application databases enriched with ML outputs without building reverse ETL pipelines manually.
Identify aging or infrequently accessed records in Azure SQL based on timestamps or business rules. Automatically move them to cost-effective Delta Lake storage in Databricks while maintaining query access through the lakehouse.
Maintain reference data, aggregated metrics, or curated dimension tables in Databricks, then automatically sync them to Azure SQL to power application queries, dashboards, or operational reports that need low-latency access.
Monitor Databricks pipeline runs and job statuses that feed data back to Azure SQL. When jobs fail or produce unexpected results, automatically notify teams and pause downstream Azure SQL updates to prevent bad data propagation.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Azure SQL and Databricks 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 both Azure SQL's relational schema and Databricks' lakehouse structures—mapping between T-SQL tables and Delta Lake formats without manual configuration.
Redbird automatically maps Azure SQL data types, constraints, and indexes to Databricks Delta table schemas and partition strategies. It detects primary keys, foreign key relationships, and computed columns in Azure SQL, then intelligently structures Delta tables with appropriate partitioning, clustering, and optimization hints. When schemas evolve—new columns, type changes, or constraint updates—Redbird reconciles differences and handles migrations without breaking pipelines.
faster than building Azure Data Factory pipelines with custom merge logic
Redbird can pull from Azure SQL and Databricks 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 Azure SQL or Databricks.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Azure SQL into Databricks, or from Databricks back into Azure SQL. 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 any event in Azure SQL or Databricks—new records, schema changes, job completions, or query patterns.
Detect inserts, updates, or deletes in Azure SQL tables using change tracking or timestamp columns.
Monitor when columns are added, removed, or modified in Azure SQL database schemas.
Trigger when specific queries take longer than expected or return unexpected row counts.
Write new records or update existing ones in Azure SQL tables with merge logic.
Run Azure SQL stored procedures with parameters to trigger business logic or data processing.
Move or flag records in Azure SQL tables based on age, status, or business rules.
Detect when notebooks, Delta Live Tables pipelines, or scheduled jobs finish successfully or fail.
Monitor when new files or records appear in specific Delta Lake tables or paths.
Trigger when ML model accuracy, drift scores, or training metrics reach specified values.
Execute Databricks notebooks or workflows with parameters to process data or train models.
Insert, merge, or overwrite data in Delta Lake tables with schema enforcement and optimization.
Publish computed features or feature values to Databricks Feature Store for model serving.
Join data teams using Redbird to automate Azure SQL and Databricks integration. Stop building and maintaining custom ETL pipelines—start automating the flow between operational databases and your lakehouse platform.