Redbird AI automates data movement and transformation between Google's cloud data warehouse and your Microsoft enterprise databases. Stop writing custom ETL scripts, managing scheduled jobs, and manually reconciling data between GCP and on-premise systems.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically capture inserts, updates, and deletes from SQL Server tables and sync them to BigQuery staging tables. Redbird handles schema mapping, data type conversion, and incremental loads so your analytics warehouse stays current with operational data.
Run machine learning models in BigQuery and write scored predictions directly to SQL Server tables that power production applications. Enable real-time personalization, risk scoring, and forecasting without building separate prediction infrastructure.
Keep dimension tables, lookup values, and reference data synchronized from SQL Server to BigQuery. Redbird detects changes in master data tables and propagates updates, ensuring analysts can join operational context without cross-platform queries.
Move historical transactional data from expensive SQL Server storage to cost-effective BigQuery cold storage based on retention policies. Maintain query access to complete history while reducing database footprint and licensing costs.
Pre-calculate analytics, KPIs, and summary tables in BigQuery then write results back to SQL Server for consumption by .NET applications, stored procedures, and Power BI. Offload heavy analytical processing while keeping results accessible to enterprise tools.
Run anomaly detection queries in BigQuery and write flagged records to SQL Server alert tables that trigger enterprise notification workflows. Bridge cloud analytics with on-premise monitoring and incident management systems.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and SQL Server 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 BigQuery's nested and repeated fields and SQL Server's relational constraints, automatically handling the structural and type mismatches between Google's cloud warehouse and Microsoft's enterprise database.
Redbird's AI automatically maps between BigQuery's standard SQL and SQL Server's T-SQL syntax, handling differences in window functions, date arithmetic, and type systems. It intelligently flattens BigQuery's nested STRUCT and ARRAY types into normalized SQL Server tables, while respecting foreign keys, indexes, and constraints. When moving data to BigQuery, Redbird optimizes for partitioning and clustering strategies that match your query patterns, translating SQL Server's relational design into warehouse-native structures.
faster than building custom SSIS packages and Cloud Dataflow jobs
Redbird can pull from BigQuery and SQL Server 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 BigQuery or SQL Server.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from BigQuery into SQL Server, or from SQL Server back into BigQuery. 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 query completion in BigQuery or row changes in SQL Server—Redbird connects both platforms in either direction.
Trigger when a BigQuery scheduled query finishes running, capturing new analytical results.
Detect when new date or ingestion-time partitions are created in partitioned tables.
Respond when real-time streaming inserts accumulate to specified thresholds in BigQuery tables.
Execute a SQL query and persist results to a new or existing BigQuery table with specified partitioning.
Insert, append, or overwrite rows in BigQuery tables with automatic schema detection and evolution.
Create or update partitioned target tables optimized for time-series or categorical analysis patterns.
Capture change data when rows are added or modified in specified SQL Server tables.
Trigger when specific stored procedures finish execution, capturing business process completions.
Respond when transaction log activity reaches specified volume, indicating high-velocity changes.
Write large datasets to SQL Server tables using optimized bulk insert operations with transaction control.
Call SQL Server stored procedures with parameters, triggering business logic and database operations.
Update existing records or insert new ones based on key matching, maintaining data consistency.
Stop building point-to-point pipelines between BigQuery and SQL Server. Redbird AI connects your Google cloud warehouse with Microsoft enterprise databases in minutes, not sprints.