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Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Datadog connector details
The Datadog connector captures observability data such as logs and RUM (Real User Monitoring) events from Datadog into Estuary Flow 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 Flow to power advanced reliability dashboards and alerting systems.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes from Datadog in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your Datadog insights always reflect the latest data by connecting your databases to Datadog with change data capture.
- Or connect critical SaaS apps to Datadog with real-time data pipelines.
Don't see a connector?Request and our team will get back to you in 24 hours
Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
Deliver real-time and batch data from DBs, SaaS, APIs, and more
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