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Amazon RDS to AWS Aurora PostgreSQL integration — real-time, two-way sync

Keep Amazon RDS and AWS Aurora PostgreSQL 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 Amazon RDS and AWS Aurora PostgreSQL

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

Teams connect Amazon RDS and AWS Aurora PostgreSQL to keep relational data consistent across engines or environments — for migrations, environment sync, or workload separation. Tables, Rows, and Views and materialized views replicate with Primary keys and constraints intact on both sides.

Stacksync syncs tables or collections between Amazon RDS and AWS Aurora PostgreSQL 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 from RDS to Aurora PostgreSQL incrementally while both databases serve traffic.
  • 02 Enforce consistent Columns and Primary keys and constraints across replicated Schemas.
  • 03 Serve read-heavy workloads from Aurora PostgreSQL without loading the RDS primary.
  • 04 Keep an RDS reporting database hydrated from operational tools without maintaining ETL jobs

Common sync patterns

Two-way table sync

RDS Tables and Aurora PostgreSQL Tables exchange Rows continuously with conflict-safe keys.

Environment mirroring

selected Databases and schemas replicate from a production RDS instance into Aurora PostgreSQL for staging.

Materialized reporting layer

data synced into Aurora PostgreSQL feeds Views and materialized views for analytics.

What you can sync between Amazon RDS and AWS Aurora PostgreSQL

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.

Amazon RDS objects AWS Aurora PostgreSQL objects How this pairing syncs
Tables The core sync target; rows map to records in connected SaaS systems. Tables The core sync unit; rows are matched across systems by primary key. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Columns Field-level mapping targets, typed per the underlying engine. Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces within a database used to isolate synced tables. Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Schemas is specific to Amazon RDS and Views and materialized views to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Views Read-side projections exposed to outbound syncs. Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Views is specific to Amazon RDS and Foreign keys to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Primary and Unique Keys Match keys for idempotent upserts. Replication slots and publications The logical replication objects that power log-based CDC. Primary and Unique Keys is specific to Amazon RDS and Replication slots and publications to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Read Replicas Low-impact read endpoints often used as the source side of a sync. Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. Read Replicas is specific to Amazon RDS and Databases and schemas to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between Amazon RDS and AWS Aurora PostgreSQL

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.

Amazon RDS AWS Aurora PostgreSQL Sub-second propagation

DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.

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

AWS Aurora PostgreSQL Amazon RDS Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

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

Rate-limit considerations

  • Amazon RDS: No API rate limits; throughput depends on instance class, storage IOPS, and connection limits.
What ships with Amazon RDS ⇄ AWS Aurora PostgreSQL

Connect Amazon RDS and AWS Aurora PostgreSQL for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon RDS or AWS Aurora PostgreSQL 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 Amazon RDS or AWS Aurora PostgreSQL record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon RDS and AWS Aurora PostgreSQL.

How the Amazon RDS and AWS Aurora PostgreSQL connectors work

Amazon RDS

Integration surface
SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle)
Authentication
Database credentials over SSL/TLS, or IAM database authentication on supported engines
Change detection
Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC; enabled through RDS parameter groups, with polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance class, storage IOPS, and connection limits

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC
How it works

How to connect Amazon RDS to AWS Aurora PostgreSQL — 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 Amazon RDS and AWS Aurora PostgreSQL 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
    Amazon RDS connected
    AWS Aurora PostgreSQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon RDS and AWS Aurora PostgreSQL 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 · Amazon RDS ⇄ AWS Aurora PostgreSQL
    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
    Amazon RDS AWS Aurora PostgreSQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon RDS and AWS Aurora PostgreSQL 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 400 integrations available for Amazon RDS and AWS Aurora PostgreSQL.

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