Stream data from Snowflake Data Cloud to MongoDB

Estuary’s Snowflake connector enables incremental data capture from Snowflake tables using Snowflake Streams and staging tables. While it supports CDC-like change tracking (inserts, updates, and deletes), the process is polling-based, meaning data is captured at scheduled intervals rather than in true real time. This design provides a balanced approach between freshness, cost efficiency, and reliability in Snowflake environments.

• Supports insert, update, and delete detection via Snowflake Streams
• Secure JWT key-pair authentication for modern, passwordless access
• Configurable polling intervals to optimize between latency and cost
• Compatible with Snowflake Secure Data Sharing, enabling capture from shared tables
• Fully deployable in Estuary’s managed or private cloud environments with enterprise-grade security

The MongoDB materialization connector writes Estuary collections into MongoDB collections, turning each Estuary collection document into a MongoDB document. Estuary uses the Estuary collection key to create the MongoDB _id value, so documents can be updated consistently as upstream data changes.

• Materialize Estuary collections into MongoDB collections for application, operational, and real-time serving use cases.
• Create MongoDB documents with an _id value based on the Estuary collection key.
• If an Estuary collection already contains a field named _id, Estuary writes that field as _flow_id to avoid conflicts with MongoDB’s required _id field.
• Connect using your MongoDB host address, database name, username, and password, including mongodb+srv:// addresses where applicable.
• Use a MongoDB user with read and write access to the target database and collections.
• Support standard merge updates by default, with optional delta updates for workloads that need that update mode.