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

Keep AWS Aurora MySQL and Postgres Heroku 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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Migrated from Mulesoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect AWS Aurora MySQL and Postgres Heroku

Keep AWS Aurora MySQL and Postgres Heroku 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 Postgres Heroku 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

  • Give backend services read and write access to ERP or billing data by syncing it into Aurora tables the application already queries.
  • Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
  • Keep several Heroku app databases aligned with one system of record
  • Reflect billing and subscription records into the app database so product logic reads local rows

Cross-engine sync

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

Migration with zero-downtime cutover

When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.

Shared reference data between services

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

What you can sync between AWS Aurora MySQL and Postgres Heroku

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 Postgres Heroku objects
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Views Read-side projections exposed to outbound syncs.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Materialized Views Precomputed result sets synced outward on refresh.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Schemas Namespaces that scope which tables a sync reads and writes.
Views Can serve as read-only sync sources for derived or filtered datasets. Primary and Unique Keys Match keys for idempotent upserts from connected systems.
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. JSONB Columns Semi-structured payloads for nested SaaS objects and metadata.
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Sequences Generate surrogate keys for rows created by inbound syncs.
What ships with AWS Aurora MySQL ⇄ Postgres Heroku

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

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

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Postgres Heroku 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 Postgres Heroku 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 Postgres Heroku record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Postgres Heroku 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 Postgres Heroku.

How the AWS Aurora MySQL and Postgres Heroku 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

Postgres Heroku

Integration surface
SQL wire protocol (standard PostgreSQL)
Authentication
Database credentials from the Heroku DATABASE_URL config var; SSL required
Change detection
Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
Capabilities
read · write
Rate limits
No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works

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

    Choose tables

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

AWS Aurora MySQL and Postgres Heroku integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for AWS Aurora MySQL and Postgres Heroku.

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