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Database ⇄ Data warehouse

Amazon Aurora to Greenplum integration — real-time, two-way sync

Keep Amazon Aurora and Greenplum 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 Aurora and Greenplum

Connect Amazon Aurora and Greenplum 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 Amazon Aurora's rows in Greenplum, 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 Amazon Aurora where the services that read from it get them at normal query latency.

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

Common use cases

  • 01 Publish segments, scores, and aggregates computed in Greenplum back into business tools where teams act on them.
  • 02 Keep Greenplum and a cloud warehouse in sync during a migration so both platforms serve consistent data.
  • 03 Two-way sync between Aurora application tables and a CRM so product data and account data stay consistent.
  • 04 Stream row-level changes from Aurora into a warehouse for near-real-time analytics without batch exports.

Common sync patterns

Offload heavy reads

Point analytical queries at the synced copy in Greenplum and keep Amazon Aurora focused on its operational workload.

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

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

What you can sync between Amazon Aurora and Greenplum

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 Aurora objects Greenplum objects How this pairing syncs
Databases Logical databases within a cluster that scope a sync connection. Databases Top-level containers that scope a sync connection. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Schemas Namespace tables and control which objects a sync can see. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables Relational tables synced bi-directionally at row level. Tables Heap or append-optimized tables mapped directly to sync targets. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Read-only query-backed sources for downstream syncs. Views Read-only projections used to shape data before syncing it out. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. External tables Reference external files for bulk load paths alongside row-level syncs. Columns and Data Types is specific to Amazon Aurora and External tables to Greenplum — each maps to any object or custom field on the other side.
Primary and Foreign Keys Constraints used to identify records and preserve relational integrity in syncs. Rows Read and written by key; distribution keys determine where rows live. Primary and Foreign Keys is specific to Amazon Aurora and Rows to Greenplum — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora and Greenplum

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 Aurora Greenplum Sub-second propagation

DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.

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

Greenplum Amazon Aurora Interval-based propagation

DetectionStacksync polls Greenplum for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key-based cursors.

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

Rate-limit considerations

  • Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
  • Greenplum: Bounded by cluster resources and concurrency settings rather than an API quota.
What ships with Amazon Aurora ⇄ Greenplum

Connect Amazon Aurora and Greenplum for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora or Greenplum 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 Aurora or Greenplum record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Aurora and Greenplum.

How the Amazon Aurora and Greenplum connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

Greenplum

Integration surface
PostgreSQL wire protocol (libpq), plus JDBC/ODBC drivers
Authentication
Database credentials
Change detection
Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC
Capabilities
read · write
Rate limits
Bounded by cluster resources and concurrency settings rather than an API quota.
How it works

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

    Choose tables

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

Amazon Aurora and Greenplum 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 368 integrations available for Amazon Aurora and Greenplum.

Popular · 2 of 368
All Amazon Aurora integrations All Greenplum integrations Browse all integrations
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