Stream data from MySQL to Amazon Aurora for Postgres
Move data from MySQL to Amazon Aurora for Postgres in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 200+Of connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate MySQL with Amazon Aurora for Postgres in 3 simple steps
Connect MySQL as your data source
Set up a source connector for MySQL 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 Amazon Aurora for Postgres 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 Amazon Aurora for Postgres.
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.

MySQL connector details
Designed for high-throughput data pipelines, the Estuary MySQL connector captures every insert, update, and delete in real time using Change Data Capture (CDC). It reads from MySQL binary logs to ensure low-latency streaming and exactly-once delivery into Estuary collections. The connector works across self-hosted, RDS, Aurora, Cloud SQL, and Azure Database for MySQL environments with secure options like SSH tunneling and SSL.
- Continuous CDC streaming from MySQL binlogs
- Works with managed and on-prem MySQL instances
- Supports backfill for complete initial syncs
- Handles time zones and schema discovery automatically
- Secure connections via SSH or SSL

See how Livble uses MySQL

Amazon Aurora for Postgres connector details
- Merge-based materializations to sync only what's changed
- Low-latency delivery from streaming and batch sources
- Automatic schema alignment so your destination matches your pipeline's evolving data
- Flexible deployment models, including BYOC and hybrid for enterprise governance
- Unified streaming + batch outputs in a single tool
- End-to-end security and compliance for sensitive data workloads
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.

MySQL to Amazon Aurora for Postgres pricing estimate
Estimated monthly cost to move 800 GB from MySQL to Amazon Aurora for Postgres is approximately $1,000.
Data moved
Choose how much data you want to move from MySQL to Amazon Aurora for Postgres 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 MySQL to Amazon Aurora for Postgres 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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DataOps made simple
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.




































