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Amazon Seller Central to AWS Aurora PostgreSQL integration — real-time data sync

Keep Amazon Seller Central 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.

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

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Why teams connect Amazon Seller Central and AWS Aurora PostgreSQL

Mirror Amazon Seller Central's data into AWS Aurora PostgreSQL so your own code can read and write it like any other table, with changes flowing both ways in seconds.

Amazon Seller Central is a read-only source: Stacksync reads its data in real time and delivers it into AWS Aurora PostgreSQL, so AWS Aurora PostgreSQL always reflects the current state of Amazon Seller Central — without exports, scripts, or schedulers.

Connecting Amazon Seller Central to AWS Aurora PostgreSQL gives engineering teams a Postgres-native operational copy of marketplace data. Orders and Financial Events arrive as rows in Aurora PostgreSQL tables, where views and materialized views expose them to internal services without calling Amazon's APIs directly.

Stacksync mirrors Order Items, Listings / Catalog Items, FBA Inventory, Shipments from Amazon Seller Central into Primary keys and constraints, Views and materialized views, Foreign keys, Replication slots and publications in AWS Aurora PostgreSQL and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Amazon Seller Central, so the tool and the database never disagree.

Common use cases

  • 01 Serve internal order-status applications from Aurora PostgreSQL instead of Amazon's APIs.
  • 02 Enforce data integrity on marketplace records using Postgres constraints across Orders and Shipments.
  • 03 Model catalog data by joining Listings / Catalog Items rows with in-house product schemas.
  • 04 Land Amazon orders, reports, and settlement data in your warehouse or ERP as they are produced.

Common sync patterns

Orders to Postgres rows

Orders and Order Items sync into Aurora PostgreSQL tables with primary keys and constraints enforcing uniqueness per order.

Materialized inventory views

FBA Inventory syncs to base tables and feeds materialized views for fast stock-level reads.

Settlement data capture

Financial Events land in a dedicated schema for downstream reconciliation jobs.

What you can sync between Amazon Seller Central 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 Seller Central objects AWS Aurora PostgreSQL objects How this pairing syncs
FBA Inventory Fulfillable quantity by SKU, synced out for stock planning and replenishment. Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. FBA Inventory is specific to Amazon Seller Central and Primary keys and constraints to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Shipments Inbound and outbound shipment records used to track fulfillment state. Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Shipments is specific to Amazon Seller Central and Views and materialized views to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Financial Events Settlement, fee, and refund events synced to finance systems for reconciliation. Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Financial Events is specific to Amazon Seller Central and Foreign keys to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Returns Return and refund records routed to support and finance workflows. Replication slots and publications The logical replication objects that power log-based CDC. Returns is specific to Amazon Seller Central and Replication slots and publications to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Reports Asynchronous bulk exports used for large reads (orders, inventory, settlements). Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. Reports is specific to Amazon Seller Central and Databases and schemas to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.
Feeds Asynchronous bulk write channel for price, inventory, and listing updates. Tables The core sync unit; rows are matched across systems by primary key. Feeds is specific to Amazon Seller Central and Tables to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between Amazon Seller Central 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 Seller Central AWS Aurora PostgreSQL Interval-based propagation

DetectionStacksync polls Amazon Seller Central for changes on an incremental schedule, reading only records changed since the previous pass. Historical and incremental syncs (mechanism not further specified).

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 Seller Central 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.

DeliveryAmazon Seller Central does not accept inbound record writes, so this direction carries requests rather than records: Amazon Seller Central's output flows back as field updates on the originating AWS Aurora PostgreSQL records.

Rate-limit considerations

  • Amazon Seller Central: Per-operation token-bucket rate limits; bulk reads and writes should go through the asynchronous Reports and Feeds APIs instead of item-by-item calls.
What ships with Amazon Seller Central ⇄ AWS Aurora PostgreSQL

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

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

Real-time

Real-time sync

Changes in Amazon Seller Central 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 Seller Central 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 Seller Central or AWS Aurora PostgreSQL record.

Observability

Monitoring

Track your Amazon Seller Central ⇄ 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 Seller Central and AWS Aurora PostgreSQL.

How the Amazon Seller Central and AWS Aurora PostgreSQL connectors work

Amazon Seller Central

Integration surface
REST API (Selling Partner API, SP-API)
Authentication
SP-API app credentials (LWA client ID/secret, application ID, Merchant ID/Seller ID token, refresh token, region) entered into the Stacksync connection form
Change detection
Historical and incremental syncs (mechanism not further specified)
Capabilities
read
Rate limits
Per-operation token-bucket rate limits; bulk reads and writes should go through the asynchronous Reports and Feeds APIs instead of item-by-item calls
Amazon Seller Central setup guide

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

    Choose tables

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

Amazon Seller Central 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.

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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 414 integrations available for Amazon Seller Central and AWS Aurora PostgreSQL.

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