Redbird AI automates data movement and transformation between your analytical warehouse and operational document database. Stop writing custom sync scripts, managing ETL jobs, or manually exporting query results to keep your systems in sync.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Run scheduled SQL queries in BigQuery and push aggregated results directly into MongoDB collections. Your applications get pre-computed analytics without querying the warehouse. Redbird handles schema mapping from SQL result sets to document structure automatically.
Continuously capture MongoDB collection changes and append them to BigQuery tables for historical analysis. Redbird flattens nested documents into warehouse-friendly schemas while preserving the original structure. Perfect for building multi-year trend analysis on operational data.
Execute BigQuery ML models on warehouse data and write predictions back to MongoDB documents. Your application layer gets real-time access to scores, recommendations, and classifications without warehouse queries. Redbird maps prediction outputs to the right document fields and handles batch updates.
Capture user activity, transactions, and application events from MongoDB and load them into BigQuery streaming buffers. Data becomes queryable within seconds for live dashboards and operational reporting. Redbird handles schema evolution as your MongoDB documents change over time.
Run cohort analysis and segmentation queries in BigQuery, then update MongoDB user documents with segment assignments. Your application can personalize experiences based on warehouse-computed attributes without complex joins. Segments stay fresh as Redbird re-runs queries on your schedule.
Continuously sync MongoDB metrics to BigQuery, run anomaly detection queries, and trigger notifications when thresholds are breached. Redbird monitors query results and connects to your alerting stack when patterns change. Get warehouse-powered monitoring on your operational database without building pipelines.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and MongoDB 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's AI understands both SQL warehouse schemas and NoSQL document structures, automatically mapping between columnar BigQuery tables and MongoDB's flexible JSON documents.
Redbird automatically flattens nested MongoDB documents into BigQuery-compatible table schemas, handling arrays, embedded objects, and varying field types across documents. When moving data to MongoDB, it intelligently structures query results into properly nested documents that match your application's expectations. Schema drift is detected and handled automatically—new fields in MongoDB appear as columns in BigQuery, and new query outputs map to document fields without manual configuration.
Faster than building custom BigQuery-MongoDB sync scripts
Redbird can pull from BigQuery and MongoDB 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 MongoDB.
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 MongoDB, or from MongoDB 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 document changes in MongoDB—Redbird connects both systems bidirectionally.
Trigger when a BigQuery scheduled query finishes running and results are ready.
Monitor BigQuery tables and trigger when new rows are inserted above a threshold.
Run a SQL query and trigger when results match specified criteria or thresholds.
Write data from any source into BigQuery tables with automatic schema detection.
Run SQL queries with dynamic parameters passed from workflow triggers.
Provision new BigQuery datasets and tables programmatically based on workflow needs.
Trigger when documents are created or modified in specified MongoDB collections.
Monitor collection document counts and trigger when growth thresholds are exceeded.
Watch specific document fields and trigger when values change across the collection.
Insert new documents or update existing ones based on matching criteria.
Bulk update document fields across collections using MongoDB query syntax.
Copy entire collections to archive databases for data retention workflows.
Connect BigQuery and MongoDB in minutes. Redbird AI handles schema mapping, data transformation, and sync scheduling so your warehouse and operational database stay in sync without custom code.