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AWS Aurora MySQL to MySQL integration — real-time, two-way sync

Keep AWS Aurora MySQL and MySQL in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect AWS Aurora MySQL and MySQL

Keep AWS Aurora MySQL and MySQL synchronized in real time, across engines, regions, or services, in one or both directions.

Teams sync AWS Aurora MySQL with standalone MySQL to bridge AWS-managed and self-managed deployments of the same engine. Databases (Schemas), Tables, and Views stay aligned across both, which supports migrations to Aurora, external read replicas, and hybrid architectures.

Stacksync syncs tables or collections between AWS Aurora MySQL and MySQL continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.

Common use cases

  • 01 Migrate a self-managed MySQL database to Aurora with continuous sync during cutover.
  • 02 Keep an on-premises MySQL copy of Aurora data for tools that cannot reach AWS.
  • 03 Maintain identical Views and keys across development, on-prem, and Aurora environments.
  • 04 Consolidate data from multiple SaaS systems into Aurora MySQL as an operational data store for the product.

Common sync patterns

Aurora-to-MySQL replica

Aurora tables and rows replicate into a MySQL instance running outside AWS for local reads.

Migration sync

schemas, columns, and Primary and Unique Keys stay consistent while an application moves from MySQL to Aurora.

JSON column propagation

MySQL JSON Columns sync with Aurora columns so semi-structured fields match in both environments.

What you can sync between AWS Aurora MySQL and MySQL

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

AWS Aurora MySQL objects MySQL objects How this pairing syncs
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Databases (Schemas) Top-level namespaces that scope a sync's reads and writes. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Tables The primary sync target; rows map to records in connected systems. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Columns Field-level mapping targets with engine-typed values. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Can serve as read-only sync sources for derived or filtered datasets. Views Read-side projections used as outbound sync sources. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Primary and Unique Keys Match keys for idempotent upserts and conflict handling. Primary keys and indexes is specific to AWS Aurora MySQL and Primary and Unique Keys to MySQL — each maps to any object or custom field on the other side.
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. JSON Columns Validated semi-structured payloads for nested SaaS data. Foreign keys is specific to AWS Aurora MySQL and JSON Columns to MySQL — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL and MySQL

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

AWS Aurora MySQL MySQL Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

DeliveryEach detected change is applied to MySQL as a row-level write, with types converted between the two schemas.

MySQL AWS Aurora MySQL Sub-second propagation

DetectionChanges in MySQL are captured at the source via change data capture — no polling loop against its API. Database triggers — Stacksync creates deterministic triggers for internal logging and syncing (requires log_bin_trust_function_creators=ON when.

DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • MySQL: No API rate limits; throughput is bounded by connection limits and server resources.
What ships with AWS Aurora MySQL ⇄ MySQL

Connect AWS Aurora MySQL and MySQL for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–MySQL connection.

Real-time

Two-way sync

Changes in AWS Aurora MySQL or MySQL instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora MySQL or MySQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single AWS Aurora MySQL or MySQL record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ MySQL sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and MySQL.

How the AWS Aurora MySQL and MySQL connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
Capabilities
read · write · CDC

MySQL

Integration surface
SQL wire protocol (MySQL client/server protocol)
Authentication
Database credentials entered as a connection string or parameters, with optional SSL root certificate upload and optional SSH tunnel (SSH user + SSH host)
Change detection
Database triggers — Stacksync creates deterministic triggers for internal logging and syncing (requires log_bin_trust_function_creators=ON when binary logging is enabled)
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits and server resources
MySQL setup guide
How it works

How to connect AWS Aurora MySQL to MySQL — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate AWS Aurora MySQL and MySQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    AWS Aurora MySQL connected
    MySQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL and MySQL objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · AWS Aurora MySQL ⇄ MySQL
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    AWS Aurora MySQL MySQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL and MySQL integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 490 integrations available for AWS Aurora MySQL and MySQL.

Popular · 6 of 490
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