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Data warehouse ⇄ Database

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

Keep Amazon Redshift 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 Redshift and AWS Aurora PostgreSQL

Connect AWS Aurora PostgreSQL and Amazon Redshift with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want AWS Aurora PostgreSQL's rows in Amazon Redshift, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in AWS Aurora PostgreSQL where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in AWS Aurora PostgreSQL sync into Amazon Redshift in real time, and result tables in Amazon Redshift sync back into AWS Aurora PostgreSQL, with schema and type mapping between the two systems handled for you.

Common use cases

  • Publish finance rollups computed in Redshift back to spreadsheets or operational tools.
  • Feed customer 360 tables built in Redshift to support and success platforms.
  • Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
  • Feed operational dashboards from a read replica while the writer handles sync traffic.

Operational data in the warehouse, minus the pipeline

Rows from AWS Aurora PostgreSQL land in Amazon Redshift as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Amazon Redshift sync into AWS Aurora PostgreSQL, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

What you can sync between Amazon Redshift 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 Redshift objects AWS Aurora PostgreSQL objects
Databases Top-level containers within a cluster or serverless workgroup. Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets.
Schemas Namespaces used to organize synced tables and control grants. Tables The core sync unit; rows are matched across systems by primary key.
Tables Columnar tables used as sync destinations for SaaS and database data. Rows Inserted, updated, and deleted in both directions during bi-directional syncs.
Views SQL views readable as modeled sources for reverse syncs. Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields.
Materialized Views Precomputed results that downstream syncs can read for performance. Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes.
External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets.
What ships with Amazon Redshift ⇄ AWS Aurora PostgreSQL

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

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

Real-time

Two-way sync

Changes in Amazon Redshift 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 Redshift 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 Redshift or AWS Aurora PostgreSQL record.

Observability

Monitoring

Track your Amazon Redshift ⇄ 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 Redshift and AWS Aurora PostgreSQL.

How the Amazon Redshift and AWS Aurora PostgreSQL connectors work

Amazon Redshift

Integration surface
SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS
Authentication
Database credentials or IAM-based authentication
Change detection
Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers
Capabilities
read · write
Rate limits
Bounded by cluster or serverless capacity and concurrency settings rather than API quotas

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

    Choose tables

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

Amazon Redshift and AWS Aurora PostgreSQL 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 Amazon Redshift and AWS Aurora PostgreSQL.

Popular · 8 of 386
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