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- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Amazon RDS for MySQL connector details
The Amazon RDS for MySQL materialization connector streams data from Estuary Flow collections into MySQL tables hosted on Amazon RDS, enabling continuous synchronization between Flow and your managed MySQL environment.
- Supported versions: MySQL 5.7 and later
- Deployment flexibility: Connect directly or through SSH tunneling for secure private access
- Delta or standard updates: Choose between merge or delta modes for efficient data writes
- Timezone control: Supports both IANA timezone names and numeric UTC offsets for consistent datetime materialization
- Full SSL support: Configure SSL modes including verify_ca and verify_identity for secure communication
- Automatic table creation: The connector creates or updates MySQL tables as Flow collections change
- Enterprise ready: Works seamlessly within Private or BYOC deployments for compliance and governance
💡 Tip: Use this connector to stream real-time analytics or transactional data into RDS MySQL for dashboards, reporting, or downstream applications.
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 to Amazon RDS for MySQL 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 Amazon RDS for MySQL insights always reflect the latest data by connecting your databases to Amazon RDS for MySQL with change data capture.
- Or connect critical SaaS apps to Amazon RDS for MySQL with real-time data pipelines.
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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 |
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