Real-time
Two-way sync
Changes in AWS Aurora PostgreSQL or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
Database
AWS Aurora PostgreSQL to Azure SQL Database integration — real-time, two-way sync
Keep AWS Aurora PostgreSQL and Azure SQL Database 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
Live sync
stacksync.com - <1s
- latency
- 2-way
- sync
- 100M+
- records
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect AWS Aurora PostgreSQL and Azure SQL Database
Keep AWS Aurora PostgreSQL and Azure SQL Database synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between AWS Aurora PostgreSQL and Azure SQL Database continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Sync JSONB-heavy application data into structured objects in downstream business systems.
- 02 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
- 03 Replicate Azure SQL tables to a warehouse without building custom CDC pipelines.
- 04 Consolidate data from several line-of-business apps into one Azure SQL database as an integration hub.
Common sync patterns
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
What you can sync between AWS Aurora PostgreSQL and Azure SQL Database
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 | Azure SQL Database objects | How this pairing syncs | |
|---|---|---|---|
| Tables The core sync unit; rows are matched across systems by primary key. | Tables The primary sync target; rows map one-to-one to records in the paired system. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Rows and columns Standard relational records with typed columns; primary keys anchor upserts. | Foreign keys is specific to AWS Aurora PostgreSQL and Rows and columns to Azure SQL Database — 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. | Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. | Replication slots and publications is specific to AWS Aurora PostgreSQL and Stored procedures to Azure SQL Database — 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. | Change tracking / CDC tables System-maintained change records used to drive incremental sync. | Databases and schemas is specific to AWS Aurora PostgreSQL and Change tracking / CDC tables to Azure SQL Database — each maps to any object or custom field on the other side. | |
| Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | Views Read-only projections used when the sync should expose a curated shape rather than raw tables. | Rows is specific to AWS Aurora PostgreSQL and Views to Azure SQL Database — each maps to any object or custom field on the other side. | |
| Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Schemas Namespaces that organize tables and control which objects a sync user can reach. | Columns is specific to AWS Aurora PostgreSQL and Schemas to Azure SQL Database — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora PostgreSQL and Azure SQL Database
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 Azure SQL Database 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 applied to Azure SQL Database as a row-level write, with types converted between the two schemas.
Azure SQL Database AWS Aurora PostgreSQL Sub-second propagation
DetectionChanges in Azure SQL Database are captured at the source via change data capture — no polling loop against its API. Change data capture or change tracking, both supported on Azure SQL Database.
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
What ships with AWS Aurora PostgreSQL ⇄ Azure SQL Database
Connect AWS Aurora PostgreSQL and Azure SQL Database for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Azure SQL Database connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora PostgreSQL or Azure SQL Database 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 Azure SQL Database record.
Observability
Monitoring
Track your AWS Aurora PostgreSQL ⇄ Azure SQL Database 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 Azure SQL Database.
How the AWS Aurora PostgreSQL and Azure SQL Database 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
Azure SQL Database
- Integration surface
- SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
- Authentication
- SQL authentication (database credentials) or Microsoft Entra ID authentication
- Change detection
- Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
- Capabilities
- read · write · CDC
How it works
How to connect AWS Aurora PostgreSQL to Azure SQL Database — 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 Azure SQL Database 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
Azure SQL Database
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora PostgreSQL and Azure SQL Database 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 ⇄ Azure SQL DatabaseCustomers 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 Azure SQL DatabaseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora PostgreSQL and Azure SQL Database integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora PostgreSQL and Azure SQL Database: authenticate both systems, choose the objects to sync (such as AWS Aurora PostgreSQL's Tables and Foreign keys), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both AWS Aurora PostgreSQL and Azure SQL Database. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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 Azure SQL Database: Change data capture or change tracking, both supported on Azure SQL Database; 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: Columns, Primary keys and constraints, Views and materialized views, Foreign keys, plus custom fields where AWS Aurora PostgreSQL exposes them. On the Azure SQL Database side: Views, Schemas, Rows and columns, Stored procedures. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
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Common patterns for AWS Aurora PostgreSQL and Azure SQL Database: Migration with zero-downtime cutover; Shared reference data between services; Regional or environment copies. When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
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 391 integrations available for AWS Aurora PostgreSQL and Azure SQL Database.
Popular · 6 of 391
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AWS Aurora PostgreSQL ⇄ Google AlloyDB -
AWS Aurora PostgreSQL ⇄ Dynamo DB -
AWS Aurora PostgreSQL ⇄ IBM Db2 -
AWS Aurora PostgreSQL ⇄ Firebase -
Azure SQL Database ⇄ TimescaleDB -
Azure SQL Database ⇄ VoltDB
No integrations match .
