Stream data from Google Cloud SQL for MySQL to Amazon Aurora for MySQL
Move data from Google Cloud SQL for MySQL to Amazon Aurora for MySQL 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 Google Cloud SQL for MySQL with Amazon Aurora for MySQL in 3 simple steps
Connect Google Cloud SQL for MySQL as your data source
Set up a source connector for Google Cloud SQL 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 MySQL 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 MySQL.
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.

Google Cloud SQL for MySQL connector details
- Log-based CDC for high-performance, low-impact data capture
- Automatic schema evolution to handle changes in source structure without manual intervention
- Unified streaming and batch ingestion in the same pipeline
- Hybrid deployment and BYOC support for security and control
- Fault-tolerant pipelines that resume automatically from the last checkpoint
- Kafka API connectivity for direct integration into streaming ecosystems

Amazon Aurora for MySQL 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
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.

Google Cloud SQL for MySQL to Amazon Aurora for MySQL pricing estimate
Estimated monthly cost to move 800 GB from Google Cloud SQL for MySQL to Amazon Aurora for MySQL is approximately $1,000.
Data moved
Choose how much data you want to move from Google Cloud SQL for MySQL to Amazon Aurora for MySQL 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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What customers are saying
Why Estuary is the best choice for data integration
Estuary combines streaming and batch data movement capabilities into a unified modern data pipeline. This approach simplifies building and operating pipelines like Google Cloud SQL for MySQL to Amazon Aurora for MySQL without custom code or orchestration.

Increase productivity 4x
With Estuary companies increase productivity 4x and deliver new projects in days, not months. Spend much less time on troubleshooting, and much more on building new features faster. Estuary decouples sources and destinations so you can add and change systems without impacting others, and share data across analytics, apps, and AI.
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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 Google Cloud SQL for MySQL to Amazon Aurora for MySQL 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.
Related integrations with Google Cloud SQL for MySQL
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.




































