Redbird AI automates the movement of data between Azure SQL and Google Cloud Storage—no more manual exports, custom scripts, or brittle scheduled jobs. Sync database snapshots, stage tables for multi-cloud analytics, and archive operational data automatically.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically extract production tables from Azure SQL and write them to GCS as compressed Parquet files on a schedule. Redbird handles schema mapping, partitioning, and incremental updates so your data lake stays fresh without custom ETL code.
Move aged transactional records from Azure SQL into Google Cloud Storage for long-term retention. Redbird identifies rows based on timestamp columns, exports them as compressed files, and can optionally delete source records to keep your operational database lean.
Sync operational tables from Azure SQL into Google Cloud Storage as the staging layer for BigQuery ingestion. Redbird schedules exports, formats data for optimal BigQuery performance, and organizes files by date partition so your multi-cloud analytics pipeline runs seamlessly.
Create automated, timestamped snapshots of Azure SQL databases in Google Cloud Storage for cross-cloud redundancy. Redbird exports full or differential backups, compresses them, and stores them in GCS buckets with appropriate retention policies.
Ingest datasets from Google Cloud Storage into Azure SQL tables for use by Azure-hosted applications. Redbird detects new files in GCS, validates schemas, transforms data types, and inserts or upserts records into your SQL Server database automatically.
Write scoring results, predictions, or feature tables from GCS back into Azure SQL for operational use. Redbird monitors GCS buckets for new ML pipeline outputs, maps columns to SQL schema, and loads the data so applications can consume model results in real time.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Azure SQL and Google Cloud Storage 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 Azure SQL table schemas and Google Cloud Storage object structures, so it can intelligently map relational data to cloud storage formats without manual configuration.
Redbird reads Azure SQL catalogs, data types, indexes, and primary keys, then automatically determines the best file format, partitioning scheme, and compression for GCS. It handles datetime conversions, NVARCHAR to UTF-8 encoding, and DECIMAL precision mapping so your data lands intact. For reverse flows, Redbird parses CSV, JSON, and Parquet files in GCS and generates the right INSERT, UPDATE, or MERGE statements for your Azure SQL tables.
faster than building custom Python or ADF pipelines for Azure SQL to GCS syncs
Redbird can pull from Azure SQL and Google Cloud Storage 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 Google Cloud Storage.
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 Google Cloud Storage, or from Google Cloud Storage 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 database event in Azure SQL or any object change in Google Cloud Storage—Redbird connects them intelligently.
Trigger when new records are added to any Azure SQL table based on timestamp or identity columns.
Detect when existing rows are modified using change tracking or last-modified timestamps.
Run exports on a schedule—hourly, daily, or custom intervals—to capture full or incremental table states.
Write an Azure SQL table or query result to Google Cloud Storage as a compressed Parquet file.
Execute a custom SQL query in Azure SQL and export the result set to a GCS bucket as CSV or JSON.
Move historical records to GCS and optionally remove them from Azure SQL to manage database size.
Trigger when a new object is created in a Google Cloud Storage bucket or prefix.
Detect when an existing file is overwritten or modified in GCS.
Start workflows when files matching a specific prefix, suffix, or regex pattern appear in GCS.
Write the output of an Azure SQL query to a specified GCS bucket path as a structured file.
Generate a full database or table export and store it in GCS with a timestamp for versioning.
Export Azure SQL data partitioned by date column into separate GCS objects for efficient querying.
Redbird AI connects Azure SQL and Google Cloud Storage in minutes—no pipeline code, no infrastructure. Start automating cross-cloud data flows today.