Real-time
Two-way sync
Changes in Acumatica or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
ERP ⇄ Database
Acumatica to AWS Aurora PostgreSQL integration — real-time, two-way sync
Keep Acumatica 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 Acumatica and AWS Aurora PostgreSQL
Give your engineers Acumatica's data in AWS Aurora PostgreSQL: read it with normal queries, write back through the sync, and skip the ERP API entirely.
Teams sync Acumatica with AWS Aurora PostgreSQL to work with ERP data using Postgres tooling. Acumatica Vendors, Purchase Orders, and Invoices land in Aurora Tables under managed Databases and schemas, with Primary keys and constraints enforcing integrity, and edits made in Postgres flow back to Acumatica.
Stacksync mirrors Customers, Vendors, Sales Orders, Invoices from Acumatica into AWS Aurora PostgreSQL and keeps both sides consistent in real time. Whatever Acumatica is the system of record for, whether financials, operations, people, or procurement, those records become rows your code can query, and changes written in AWS Aurora PostgreSQL sync back into Acumatica with its validations respected.
Common use cases
- 01 Give data teams Postgres access to Purchase Orders and Vendors for procurement analysis
- 02 Serve internal tools from Aurora while Acumatica remains the accounting system of record
- 03 Enforce data integrity on synced ERP records using Postgres constraints
- 04 Sync JSONB-heavy application data into structured objects in downstream business systems.
Common sync patterns
ERP mirror in Postgres
Acumatica Customers and Invoices sync into Aurora Tables with Primary keys and constraints preserved
Materialized reporting
Views and materialized views over synced Sales Orders power finance dashboards without API calls
SQL-driven updates
Rows updated in Aurora Tables write back to the corresponding Acumatica Stock Items
What you can sync between Acumatica 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.
| Acumatica objects | AWS Aurora PostgreSQL objects | How this pairing syncs | |
|---|---|---|---|
| Sales Orders Order documents created from e-commerce and CRM systems, read back for fulfillment status. | Replication slots and publications The logical replication objects that power log-based CDC. | Sales Orders is specific to Acumatica and Replication slots and publications to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Invoices AR and AP billing documents synced for payment tracking and CRM visibility. | Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Invoices is specific to Acumatica and Databases and schemas to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Purchase Orders Procurement documents exchanged with supplier-facing systems. | Tables The core sync unit; rows are matched across systems by primary key. | Purchase Orders is specific to Acumatica and Tables to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Stock Items Inventory master data with quantities shared with external sales channels. | Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Stock Items is specific to Acumatica and Rows to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Shipments Fulfillment documents read to update tracking in storefronts and CRMs. | Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Shipments is specific to Acumatica and Columns to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Payments Customer payment records reconciled against invoices from payment platforms. | Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Payments is specific to Acumatica and Primary keys and constraints to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. |
How changes propagate between Acumatica 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.
Acumatica AWS Aurora PostgreSQL Sub-second propagation
DetectionAcumatica notifies Stacksync of record changes through webhook events. Push notifications configurable on data changes, plus polling on LastModifiedDateTime fields.
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
AWS Aurora PostgreSQL Acumatica 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 written to Acumatica through its API, with automatic retries and rate-limit backoff.
What ships with Acumatica ⇄ AWS Aurora PostgreSQL
Connect Acumatica and AWS Aurora PostgreSQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Acumatica–AWS Aurora PostgreSQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Acumatica 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 Acumatica or AWS Aurora PostgreSQL record.
Observability
Monitoring
Track your Acumatica ⇄ 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 Acumatica and AWS Aurora PostgreSQL.
How the Acumatica and AWS Aurora PostgreSQL connectors work
Acumatica
- Integration surface
- Contract-based REST API (JSON over versioned endpoints), plus SOAP web services and OData access to Generic Inquiries
- Authentication
- OAuth 2.0 or cookie-based session login with Acumatica credentials
- Change detection
- Push notifications configurable on data changes, plus polling on LastModifiedDateTime fields
- Capabilities
- read · write · webhooks
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 Acumatica 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.
- 01
Connect your apps
Authenticate Acumatica 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.
Acumatica
connected
AWS Aurora PostgreSQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Acumatica 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.
objects · Acumatica ⇄ AWS Aurora PostgreSQLCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Acumatica AWS Aurora PostgreSQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Acumatica and AWS Aurora PostgreSQL integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Acumatica and AWS Aurora PostgreSQL: authenticate both systems, choose the objects to sync (such as Acumatica's Sales Orders and Invoices), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Change detection on Acumatica: Push notifications configurable on data changes, plus polling on LastModifiedDateTime fields. On AWS Aurora PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the AWS Aurora PostgreSQL side: Views and materialized views, Foreign keys, Replication slots and publications, Databases and schemas, plus custom fields where AWS Aurora PostgreSQL exposes them. On the Acumatica side: Customers, Vendors, Sales Orders, Invoices. Stacksync auto-detects both schemas and converts types between the two systems.
-
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
-
Common patterns for Acumatica and AWS Aurora PostgreSQL: ERP mirror in Postgres; Materialized reporting; SQL-driven updates. Acumatica Customers and Invoices sync into Aurora Tables with Primary keys and constraints preserved
-
Acumatica: Contract-based REST API (JSON over versioned endpoints), plus SOAP web services and OData access to Generic Inquiries. Authentication: OAuth 2.0 or cookie-based session login with Acumatica credentials. AWS Aurora PostgreSQL: SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
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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→ 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:
Related integrations
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