Stream data from Oracle Database (Batch) to MongoDB
Move data from Oracle Database (Batch) to MongoDB in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 200+Connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate Oracle Database (Batch) with MongoDB in 3 simple steps
- 1
Connect Oracle Database (Batch) as your data source
Set up a source connector for Oracle Database (Batch) in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
- 2
Configure MongoDB as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to MongoDB.
- 3
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

Oracle Database (Batch) connector details
The Oracle Database Batch Query connector in Estuary captures data by periodically querying Oracle tables and views and loading the results into Estuary collections. It supports several query patterns, making it useful when LogMiner-based CDC is unavailable, when capturing from database views or read replicas, or when you need custom SQL queries.
- ROWSCN-based incremental capture using Oracle’s
ORA_ROWSCNto identify rows modified since the previous poll - Cursor-based incremental capture using fields such as update timestamps, creation timestamps, or incrementing IDs
- Full-refresh capture for tables or views without a suitable cursor
- Custom SQL queries for filtering, aggregations, or capturing specific subsets of data
- Configurable polling schedules, with a default interval of 5 minutes
- Automatic table discovery across accessible Oracle schemas
- Primary-key-aware collections, using discovered primary keys when available
- Support for Oracle Database 11g and later, including self-hosted databases, Amazon RDS, Oracle Cloud Infrastructure, and other managed platforms
For discovered tables, the connector can use ORA_ROWSCN to perform an initial full backfill and then capture only new or updated rows on subsequent polls. When no cursor is configured, the full table or view is re-read during each polling cycle.

MongoDB connector details
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
_idvalue based on the Estuary collection key. - If an Estuary collection already contains a field named
_id, Estuary writes that field as_flow_idto avoid conflicts with MongoDB’s required_idfield. - 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.
Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

Oracle Database (Batch) to MongoDB pricing estimate
Estimated monthly cost to move 800 GB from Oracle Database (Batch) to MongoDB is approximately $1,000.
Data moved
Choose how much data you want to move from Oracle Database (Batch) to MongoDB each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.



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Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this Oracle Database (Batch) to MongoDB integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
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