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

Keep Amazon RDS and 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.

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

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Why teams connect Amazon RDS and PostgreSQL

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

Syncing Amazon RDS with PostgreSQL keeps two databases aligned at the schema level: Tables, Views, and Columns replicate in both directions, with Primary and Unique Keys preserving row identity. Teams use this to bridge managed RDS instances with self-hosted or separately managed PostgreSQL environments.

Stacksync syncs tables or collections between Amazon RDS and 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 Keep a self-hosted PostgreSQL analytics environment current with production Amazon RDS Tables.
  • 02 Run a phased database migration with both sides live and Columns kept in sync until cutover.
  • 03 Consolidate Schemas from multiple RDS instances into one PostgreSQL database for unified querying.
  • 04 Use a read replica as the sync source to keep change capture load off the primary instance

Common sync patterns

Cross-database replication

Tables and Columns in Amazon RDS stay synchronized with their PostgreSQL counterparts in both directions.

Reporting replica

RDS production Schemas replicate into PostgreSQL Materialized Views so analytics load never touches the primary.

Migration bridge

Schemas, Views, and Primary and Unique Keys sync continuously while workloads move between RDS and PostgreSQL.

What you can sync between Amazon RDS and 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 PostgreSQL objects How this pairing syncs
Schemas Namespaces within a database used to isolate synced tables. Schemas Namespaces that scope which tables a sync reads and writes. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables The core sync target; rows map to records in connected SaaS systems. Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Read-side projections exposed to outbound syncs. Views Read-side projections used to expose joined or filtered data to a sync. 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 Field-level mapping targets; types are mapped to the connected system's field types. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Primary and Unique Keys Match keys for idempotent upserts. Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. Primary and Unique Keys is specific to Amazon RDS and Primary and Unique Keys to 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. JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. Read Replicas is specific to Amazon RDS and JSONB Columns to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between Amazon RDS and 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 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 PostgreSQL as a row-level write, with types converted between the two schemas.

PostgreSQL Amazon RDS Sub-second propagation

DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.

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.
  • PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
What ships with Amazon RDS ⇄ PostgreSQL

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

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

Real-time

Two-way sync

Changes in Amazon RDS or 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 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 PostgreSQL record.

Observability

Monitoring

Track your Amazon RDS ⇄ 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 PostgreSQL.

How the Amazon RDS and 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

PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL frontend/backend protocol)
Authentication
Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
Change detection
Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
PostgreSQL setup guide
How it works

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

    Choose tables

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

Amazon RDS and 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
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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 493 integrations available for Amazon RDS and PostgreSQL.

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