Redbird AI automates the pipeline between your cloud storage and document database. Stop writing custom scripts to parse files, transform data, and load documents. Let AI handle the ETL work from blob storage to MongoDB collections.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
When new JSON or JSONL files land in Azure Blob Storage, Redbird automatically parses the structure, validates schemas, and inserts documents into the appropriate MongoDB collections. No custom parsing scripts or manual data loading required.
Redbird periodically exports MongoDB collections as compressed JSON files and archives them to Azure Blob Storage with timestamp-based organization. Keep historical snapshots for compliance, recovery, or long-term analysis without bloating your operational database.
When CSV files arrive in designated blob containers, Redbird maps columns to MongoDB document fields, applies data type conversions, enriches records with reference data, and loads them into collections. Handles nested structures and array fields automatically.
Run scheduled MongoDB aggregations and export results as optimized Parquet files in Azure Blob Storage. Makes operational data immediately available to downstream analytics tools, data warehouses, and BI platforms without impacting production database performance.
Stream application logs, event data, and telemetry files from Azure Blob Storage into MongoDB collections as they arrive. Redbird parses log formats, extracts structured fields, and indexes documents for fast querying by your engineering and operations teams.
Redbird monitors incoming blob files and detects when field structures or data types don't match existing MongoDB schemas. Automatically notifies data teams when new fields appear or validation rules are violated, preventing failed imports and data quality issues.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Azure Blob 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 AI understands both blob storage file structures and MongoDB document schemas, so you can move data between unstructured cloud storage and flexible NoSQL collections without writing transformation code.
Redbird automatically detects file formats in Azure Blob Storage—JSON, CSV, Parquet, logs, or nested structures—and maps them to MongoDB document schemas. It understands embedded arrays, nested objects, and flexible field types, handling schema evolution as your data changes. The AI infers data types, validates against MongoDB constraints, and optimizes batch inserts for throughput. Whether you're loading raw event streams or structured application data, Redbird bridges blob storage and document databases intelligently.
faster than building custom blob-to-MongoDB ETL pipelines
Redbird can pull from Azure Blob 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 Azure Blob 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 Azure Blob Storage into MongoDB, or from MongoDB back into Azure Blob 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 new blobs in Azure Storage or document changes in MongoDB, then take action across both systems.
Trigger when a new file appears in a specified Azure Blob Storage container or path prefix.
Detect when an existing blob is updated, overwritten, or a new version is created.
Trigger when blob names match specific patterns like date formats, file types, or naming conventions.
Retrieve file contents from Azure Blob Storage and parse JSON, CSV, Parquet, or other structured formats.
Create new blobs or overwrite existing files in Azure Blob Storage with transformed data or export results.
Copy, move, or organize blobs across containers and storage tiers for archival and lifecycle management.
Trigger when a new document is added to a specified MongoDB collection.
Detect when existing documents are updated, with optional filtering by specific field changes.
Run MongoDB aggregation pipelines on a schedule and trigger workflows with the result set.
Write new documents to MongoDB collections with automatic schema validation and indexing.
Find and update existing MongoDB documents based on query criteria, updating specific fields or entire documents.
Execute complex MongoDB aggregation pipelines and return structured results for downstream processing.
Redbird AI makes it easy to sync Azure Blob Storage with MongoDB. Build automated data pipelines between cloud storage and document databases in minutes, not weeks.