Stream data from Datadog to MongoDB
Move data from Datadog 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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- 30-day free trial


- 200+Of connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate Datadog with MongoDB in 3 simple steps
Connect Datadog as your data source
Set up a source connector for Datadog 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.
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.
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.

Datadog connector details
The Datadog connector captures observability data such as logs and RUM (Real User Monitoring) events from Datadog into Estuary collections, enabling unified visibility across your infrastructure and application analytics.
- Supported resources: real_user_monitoring, logs
- Authentication: Secure connection using Datadog API Key and Application Key with rum_apps_read and logs_read_data permissions
- Backfill options: Supports historical data sync starting from a defined date or Datadog’s default 30-day retention window
- Incremental updates: Configurable sync window for near-real-time data refresh
- Secure deployment: Fully compatible with Estuary’s Private and BYOC environments for compliance and governance
💡 Tip: Combine Datadog logs and metrics with other operational data in Estuary to power advanced reliability dashboards and alerting systems.

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.

Datadog to MongoDB pricing estimate
Estimated monthly cost to move 800 GB from Datadog to MongoDB is approximately $1,000.
Data moved
Choose how much data you want to move from Datadog 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 Datadog 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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Add advanced capabilities like schema inference and evolution with a few clicks. Or automate your data pipeline and integrate into your existing DataOps using Estuary's rich CLI.






































