Stream data from Apache Kafka to Amazon Aurora for MySQL
Move data from Apache Kafka 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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- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate Apache Kafka with Amazon Aurora for MySQL in 3 simple steps
Connect Apache Kafka as your data source
Set up a source connector for Apache Kafka 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.

Apache Kafka connector details
The Apache Kafka connector captures high-volume streaming data from Kafka topics into Estuary collections with support for both Avro and JSON message formats. It integrates seamlessly with Schema Registry for schema discovery and exactly-once delivery across distributed topics.
- Captures real-time Kafka streams from multiple topics
- Supports Avro and JSON message formats
- Integrates with Schema Registry for key and schema management
- Compatible with SASL/SCRAM, AWS IAM, and TLS authentication
- Secure deployment within Estuary’s Private and BYOC environments for compliance and governance
💡 Tip: Works with Confluent Cloud, AWS MSK, and other managed Kafka services. For best results, enable TLS and schema registry support to maintain schema integrity.

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
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.

Apache Kafka to Amazon Aurora for MySQL pricing estimate
Estimated monthly cost to move 800 GB from Apache Kafka to Amazon Aurora for MySQL is approximately $1,000.
Data moved
Choose how much data you want to move from Apache Kafka to Amazon Aurora for MySQL each month.
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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 Apache Kafka 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.
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