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

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

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

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Why teams connect AWS Aurora MySQL and Google AlloyDB

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

Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.

Stacksync syncs tables or collections between AWS Aurora MySQL and Google AlloyDB 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 Give backend services read and write access to ERP or billing data by syncing it into Aurora tables the application already queries.
  • 02 Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
  • 03 Consolidate SaaS data into AlloyDB and serve analytics from its columnar engine without a separate OLAP store.
  • 04 Migrate workloads from self-managed Postgres while keeping existing syncs pointed at a compatible endpoint.

Common sync patterns

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

Regional or environment copies

Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.

Cross-engine sync

Keep the same dataset live in both AWS Aurora MySQL and Google AlloyDB, so each workload runs on the engine that suits it.

What you can sync between AWS Aurora MySQL and Google AlloyDB

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 Google AlloyDB objects How this pairing syncs
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Tables Primary read/write target for bi-directional sync with CRMs and other systems. 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 Curated projections used as read-only sync sources. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Indexes Keep sync key lookups fast on high-volume tables. Rows is specific to AWS Aurora MySQL and Indexes to Google AlloyDB — each maps to any object or custom field on the other side.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Sequences ID generation relevant when external systems insert rows. Columns is specific to AWS Aurora MySQL and Sequences to Google AlloyDB — each maps to any object or custom field on the other side.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Replication Slots Logical replication artifacts that back log-based change capture. Primary keys and indexes is specific to AWS Aurora MySQL and Replication Slots to Google AlloyDB — 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. Databases Standard PostgreSQL databases within an AlloyDB cluster that syncs connect to. Foreign keys is specific to AWS Aurora MySQL and Databases to Google AlloyDB — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL and Google AlloyDB

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 Google AlloyDB 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 Google AlloyDB as a row-level write, with types converted between the two schemas.

Google AlloyDB AWS Aurora MySQL Sub-second propagation

DetectionChanges in Google AlloyDB are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication.

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

Rate-limit considerations

  • Google AlloyDB: No API-style rate limits; throughput is bounded by instance size.
What ships with AWS Aurora MySQL ⇄ Google AlloyDB

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

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

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Google AlloyDB 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 Google AlloyDB 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 Google AlloyDB record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Google AlloyDB 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 Google AlloyDB.

How the AWS Aurora MySQL and Google AlloyDB 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

Google AlloyDB

Integration surface
SQL wire protocol (PostgreSQL-compatible), with connectivity through the AlloyDB Auth Proxy or private IP
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC via PostgreSQL logical replication; polling on timestamp columns as a fallback
Capabilities
read · write · CDC
Rate limits
No API-style rate limits; throughput is bounded by instance size
How it works

How to connect AWS Aurora MySQL to Google AlloyDB — 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 Google AlloyDB 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
    Google AlloyDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL and Google AlloyDB 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 ⇄ Google AlloyDB
    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 Google AlloyDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL and Google AlloyDB 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 391 integrations available for AWS Aurora MySQL and Google AlloyDB.

Popular · 4 of 391
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