Real-time
Two-way sync
Changes in AWS Aurora PostgreSQL or Deposco instantly reflect in both systems. No stale data, no manual imports.
.png){kind=small}
Database ⇄ ERP
AWS Aurora PostgreSQL to Deposco integration — real-time, two-way sync
Keep AWS Aurora PostgreSQL and Deposco 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect AWS Aurora PostgreSQL and Deposco
Give your engineers Deposco's data in AWS Aurora PostgreSQL: read it with normal queries, write back through the sync, and skip the ERP API entirely.
ERP data sits behind interfaces built for the ERP's own modules, not for your internal systems. Teams that need those records, for reporting services, internal tools, or automations, end up writing integration code against a strict API and maintaining it through every upgrade.
Stacksync mirrors Purchase orders / ASNs, Receipts, Warehouses / Locations, Customers from Deposco into AWS Aurora PostgreSQL and keeps both sides consistent in real time. Whatever Deposco 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 Deposco with its validations respected.
Common use cases
- 01 Feed operational dashboards from a read replica while the writer handles sync traffic.
- 02 Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
- 03 Sync order status and shipment tracking from Deposco back to a CRM or customer portal so support sees fulfillment state.
- 04 Push sales orders from an ERP or e-commerce platform into Deposco for warehouse fulfillment.
Common sync patterns
Internal tools and automations without API code
Scripts and services read and write the synced tables; Stacksync handles the Deposco interface, limits, and retries.
React to ERP changes
Updates in Deposco arrive as row changes in AWS Aurora PostgreSQL, so jobs and triggers can respond as the business record changes.
Where Deposco is the HR system of record: people data for internal systems
Worker and org records stay current in AWS Aurora PostgreSQL for provisioning, access, and reporting systems that read from the database.
What you can sync between AWS Aurora PostgreSQL and Deposco
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 | Deposco objects | How this pairing syncs | |
|---|---|---|---|
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Inventory On-hand and available quantities by warehouse and location, read frequently by storefront syncs. | Columns is specific to AWS Aurora PostgreSQL and Inventory to Deposco — 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. | Sales orders Orders flowing in from ERP or e-commerce systems for fulfillment. | Primary keys and constraints is specific to AWS Aurora PostgreSQL and Sales orders to Deposco — 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. | Shipments Outbound shipment and tracking records synced back to order-origin systems. | Views and materialized views is specific to AWS Aurora PostgreSQL and Shipments to Deposco — each maps to any object or custom field on the other side. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Purchase orders / ASNs Inbound expectations used to plan receiving. | Foreign keys is specific to AWS Aurora PostgreSQL and Purchase orders / ASNs to Deposco — each maps to any object or custom field on the other side. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | Receipts Confirmation of received inventory that updates stock positions. | Replication slots and publications is specific to AWS Aurora PostgreSQL and Receipts to Deposco — each maps to any object or custom field on the other side. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Warehouses / Locations Facility and bin structures that scope inventory records. | Databases and schemas is specific to AWS Aurora PostgreSQL and Warehouses / Locations to Deposco — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora PostgreSQL and Deposco
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 Deposco 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 Deposco through its API, with automatic retries and rate-limit backoff.
Deposco AWS Aurora PostgreSQL Interval-based propagation
DetectionStacksync polls Deposco for changes on an incremental schedule, reading only records changed since the previous pass. Polling on order and inventory endpoints, subject to the platform's integration patterns.
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Deposco: Subject to the platform's API rate limits.
What ships with AWS Aurora PostgreSQL ⇄ Deposco
Connect AWS Aurora PostgreSQL and Deposco for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Deposco connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora PostgreSQL or Deposco 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 Deposco record.
Observability
Monitoring
Track your AWS Aurora PostgreSQL ⇄ Deposco 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 Deposco.
How the AWS Aurora PostgreSQL and Deposco 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
Deposco
- Integration surface
- REST API plus file-based interfaces (EDI and flat file) common to WMS integrations
- Authentication
- API credentials issued per integration (API key or basic authentication)
- Change detection
- Polling on order and inventory endpoints, subject to the platform's integration patterns
- Capabilities
- read · write
- Rate limits
- Subject to the platform's API rate limits
How it works
How to connect AWS Aurora PostgreSQL to Deposco — 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 AWS Aurora PostgreSQL and Deposco with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
AWS Aurora PostgreSQL
connected
Deposco
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora PostgreSQL and Deposco 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 · AWS Aurora PostgreSQL ⇄ DeposcoCustomers 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.
AWS Aurora PostgreSQL DeposcoCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora PostgreSQL and Deposco integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and Deposco: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Columns and Primary keys and constraints), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
AWS Aurora PostgreSQL: Logical replication uses publications and replication slots, so CDC reads changes from the write-ahead log without polling production tables. Deposco: Deposco's Bright Suite combines warehouse management, order management, and fulfillment in one platform, so order, inventory, and shipment data share a single system of record. Stacksync's field mapping accounts for these differences between AWS Aurora PostgreSQL and Deposco without custom code.
-
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means AWS Aurora PostgreSQL and Deposco records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS Aurora PostgreSQL and Deposco connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora PostgreSQL–Deposco integration in-house.
-
Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and Deposco. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on AWS Aurora PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback. On Deposco: Polling on order and inventory endpoints, subject to the platform's integration patterns. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 245 integrations available for AWS Aurora PostgreSQL and Deposco.
Popular · 1 of 245
No integrations match .
