Two-way sync
Changes in AWS Aurora PostgreSQL or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
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.
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.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
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 | |
|---|---|---|
| Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Schemas Namespaces that organize tables and control which objects a sync user can reach. | |
| Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Rows and columns Standard relational records with typed columns; primary keys anchor upserts. | |
| Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. | |
| Replication slots and publications The logical replication objects that power log-based CDC. | Change tracking / CDC tables System-maintained change records used to drive incremental sync. | |
| Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Tables The primary sync target; rows map one-to-one to records in the paired system. | |
| Tables The core sync unit; rows are matched across systems by primary key. | Views Read-only projections used when the sync should expose a curated shape rather than raw tables. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Azure SQL Database connection.
Changes in AWS Aurora PostgreSQL or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
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.
Handle millions of events per minute without losing a single AWS Aurora PostgreSQL or Azure SQL Database record.
Track your AWS Aurora PostgreSQL ⇄ Azure SQL Database sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Azure SQL Database.
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.
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.
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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
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 Primary keys and constraints and Views and materialized views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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.
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.
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.
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 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.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for AWS Aurora PostgreSQL and Azure SQL Database.