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FASTEST, MOST RELIABLE CDC AND ETL

Stream data from PostgreSQL to Amazon Aurora for MySQL

Move data from PostgreSQL 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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  • 30-day free trial
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  • 200+Of connectors
  • 5500+Active users
  • <100msEnd-to-end latency
  • 7+GB/secSingle dataflow

How to integrate PostgreSQL with Amazon Aurora for MySQL in 3 simple steps

1

Connect PostgreSQL as your data source

Set up a source connector for PostgreSQL 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.

2

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.

3

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.

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PostgreSQL connector details

Built for real-time data integration, the Estuary PostgreSQL connector streams inserts, updates, and deletes from PostgreSQL databases using Change Data Capture (CDC) via logical replication. It reads directly from the write-ahead log (WAL) to deliver low-latency, exactly-once data movement into Estuary collections. The connector supports self-hosted, RDS, Aurora, Cloud SQL, Azure Database for PostgreSQL, and Supabase, with secure connectivity options such as SSH tunneling and SSL.

  • Continuous CDC streaming through PostgreSQL logical replication
  • Works with managed and on-prem PostgreSQL instances
  • Supports backfill and read-only captures
  • Automatically manages replication slots and publications
  • Secure setup via SSH or SSL
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See how Curri uses PostgreSQL

For more details about the PostgreSQL connector, check out the documentation page.

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Amazon Aurora for MySQL connector details

The Amazon Aurora for MySQL materialization connector in Estuary delivers data from your pipelines directly into your destination system — continuously and in real time. Using merge-based writes, Estuary efficiently updates only changed records, ensuring your destination stays perfectly in sync without unnecessary reprocessing. Whether for analytics, AI, or operational use cases, Estuary provides a reliable, cost-efficient way to keep Amazon Aurora for MySQL up to date.
  • 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

For more details about the Amazon Aurora for MySQL connector, check out the documentation page.

Estuary in action

See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.

Success stories

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.

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PostgreSQL to Amazon Aurora for MySQL pricing estimate

$1,000 / month
800 GB of data moved
2 connector instances

Estimated monthly cost to move 800 GB from PostgreSQL to Amazon Aurora for MySQL is approximately $1,000.

Data moved

Choose how much data you want to move from PostgreSQL to Amazon Aurora for MySQL each month.

GB

Choose number of sources and destinations.

US VS THE REST

Why pay more?

Move the same data for a fraction of the cost.

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What customers are saying

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Revunit


Estuary is our preferred CDC solution for importing data from application databases into BigQuery for analytics. It offers a transparent pricing structure, timely support responses, and an intuitive CLI tool for bulk configuration tasks. In contrast, other market solutions often have ambiguous pricing and fewer options for precise data replication across environments. This makes choosing to use Estuary an obvious decision.

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DeepSync


Estuary allows us to integrate low-latency CDC and connect to SaaS apps across our entire reporting stack and it’s the only solution that we’ve found that lets us do both.

Getting started with Estuary

  • Free account

    Getting started with Estuary is simple. Sign up for a free account.

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  • Docs

    Make sure you read through the documentation, especially the get started section.

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  • Community

    Join the Slack community for the easiest way to get support while getting started.

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  • Estuary 101

    Watch the Estuary 101 webinar for a guided introduction to using Estuary.

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QUESTIONS? FEEL FREE TO CONTACT US ANY TIME!

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Frequently Asked Questions

    How is pricing calculated for moving data from PostgreSQL to Amazon Aurora for MySQL?

    Pricing is based on the volume of data moved and the number of active connectors. Use the pricing estimator above to see an estimated monthly cost for your PostgreSQL to Amazon Aurora for MySQL pipeline.

    Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.

    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.

    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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