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

Keep AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL and PostgreSQL

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

Connecting AWS Aurora PostgreSQL with self-managed or otherwise hosted PostgreSQL keeps two Postgres environments consistent — Tables, Schemas, Columns, and Views on both sides. Teams use this for migrations to Aurora, cross-environment replication, and keeping a managed copy of an on-prem database.

Stacksync syncs tables or collections between AWS Aurora PostgreSQL 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 Migrate an existing PostgreSQL instance to Aurora with continuous row-level sync instead of a one-time dump.
  • 02 Serve read workloads from Aurora while the source PostgreSQL remains the system of record.
  • 03 Keep schemas and columns aligned across production and analytics Postgres instances.
  • 04 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.

Common sync patterns

Aurora migration sync

PostgreSQL Tables, Schemas, and Primary and Unique Keys replicate into Aurora with rows kept current during cutover.

Two-way environment sync

changes to rows in either database propagate to the other, preserving columns and constraints.

View replication

Views and Materialized Views mirror across databases so reporting layers stay identical.

What you can sync between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL objects PostgreSQL objects How this pairing syncs
Tables The core sync unit; rows are matched across systems by primary key. 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.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. 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.
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. Materialized Views Precomputed result sets synced outward on a refresh schedule. Databases and schemas is specific to AWS Aurora PostgreSQL and Materialized Views to PostgreSQL — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. Schemas Namespaces that scope which tables a sync reads and writes. Rows is specific to AWS Aurora PostgreSQL and Schemas to PostgreSQL — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Primary and Unique Keys to PostgreSQL — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. Views and materialized views is specific to AWS Aurora PostgreSQL and JSONB Columns to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL PostgreSQL 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 PostgreSQL as a row-level write, with types converted between the two schemas.

PostgreSQL AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

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

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ PostgreSQL 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 PostgreSQL and PostgreSQL.

How the AWS Aurora PostgreSQL and PostgreSQL connectors work

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

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

    Choose tables

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

AWS Aurora PostgreSQL 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
HIPAA BAA
GDPR
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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 491 integrations available for AWS Aurora PostgreSQL and PostgreSQL.

Popular · 7 of 491
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