Redbird AI syncs data between your GCP storage layer and MongoDB clusters automatically. Stop writing custom scripts to move JSON files, parse CSVs into documents, or manually trigger imports when new data lands in Cloud Storage.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
When files land in a Cloud Storage bucket, Redbird parses the structure and writes documents to the appropriate MongoDB collection. Handles nested objects, arrays, and field mapping without transformation code. Ideal for event streams, application logs, and API response archives.
Schedule daily or weekly exports of production MongoDB collections to Cloud Storage in compressed JSONL or Parquet format. Redbird handles incremental exports, partitioning by date, and applies GCS lifecycle policies for cost-efficient archival.
Parse CSV files from Cloud Storage, validate against your MongoDB schema, and insert as properly typed documents. Redbird detects column types, handles missing values, and enriches rows with metadata before writing to collections.
Pull the latest dataset versions from your GCS data lake and populate MongoDB collections for operational analytics. Redbird orchestrates the full pipeline: detect new snapshots, parse partitioned data, deduplicate, and bulk-write to target collections.
Capture real-time document changes from MongoDB change streams and persist to Cloud Storage buckets organized by timestamp. Maintains immutable audit logs and enables point-in-time recovery without impacting production database performance.
When Vertex AI or other ML workflows write prediction files to Cloud Storage, Redbird automatically enriches corresponding MongoDB documents with scores, classifications, or embeddings. Keeps operational data in sync with batch inference results.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Google Cloud Storage 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 understands GCS bucket structures, object metadata, and file formats alongside MongoDB's document schemas, indexes, and collection patterns.
Redbird interprets GCS bucket hierarchies, file naming conventions, and nested folder structures, then maps them intelligently to MongoDB database and collection layouts. It infers schema from JSON files, handles BSON type conversions automatically, and respects MongoDB unique indexes and validation rules. Whether you're moving structured CSVs, semi-structured JSON, or nested application logs, Redbird adapts to your data shape without brittle transformation scripts.
faster than building custom GCS-to-MongoDB ETL jobs with Cloud Functions and MongoDB drivers
Redbird can pull from Google Cloud Storage 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 Google Cloud Storage 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 Google Cloud Storage into MongoDB, or from MongoDB back into Google Cloud Storage. 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 file event in Cloud Storage or document change in MongoDB, then route data exactly where it needs to go.
Trigger when any file or specific file patterns are uploaded to a GCS bucket or folder path.
Detect when an existing object in Cloud Storage is modified or replaced with a new version.
Run on a schedule to check for new or changed files matching specific criteria in GCS.
Fetch file from Cloud Storage and parse JSON, CSV, or JSONL into structured records.
Write new files or append to existing objects in Cloud Storage with custom metadata.
Relocate objects between buckets or folders and apply storage class changes for archival.
Trigger when a new document is added to a specific MongoDB collection.
Detect when fields in an existing document are modified using MongoDB change streams.
Run an aggregation pipeline on a schedule and trigger when results meet specified criteria.
Write single or bulk documents to a MongoDB collection with automatic schema validation.
Modify documents based on query filters using updateOne, updateMany, or upsert operations.
Execute complex queries with grouping, filtering, and transformation stages across collections.
See how Redbird can sync Google Cloud Storage and MongoDB in minutes. Build the pipelines your data engineers have been meaning to automate.