Two-way sync
Changes in AWS Aurora MySQL or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora MySQL 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 MySQL 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.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Keep the same dataset live in both AWS Aurora MySQL and Azure SQL Database, so each workload runs on the engine that suits it.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
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 MySQL objects | Azure SQL Database objects | |
|---|---|---|
| Views Can serve as read-only sync sources for derived or filtered datasets. | Schemas Namespaces that organize tables and control which objects a sync user can reach. | |
| Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | Rows and columns Standard relational records with typed columns; primary keys anchor upserts. | |
| Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. | |
| Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Change tracking / CDC tables System-maintained change records used to drive incremental sync. | |
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Tables The primary sync target; rows map one-to-one to records in the paired system. | |
| Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | 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 MySQL–Azure SQL Database connection.
Changes in AWS Aurora MySQL or Azure SQL Database instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora MySQL 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 MySQL or Azure SQL Database record.
Track your AWS Aurora MySQL ⇄ 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 MySQL 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 MySQL 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 MySQL 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 MySQL and Azure SQL Database: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Views and Foreign keys), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the AWS Aurora MySQL side: Views, Foreign keys, Stored procedures and triggers, Databases (schemas), plus custom fields where AWS Aurora MySQL exposes them. On the Azure SQL Database side: Change tracking / CDC tables, Tables, Views, Schemas. 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 MySQL and Azure SQL Database: Regional or environment copies; Cross-engine sync; Migration with zero-downtime cutover. Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. Azure SQL Database: 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. Stacksync manages authentication, retries, and rate limits on both sides.
AWS Aurora MySQL: Binlog-based CDC requires binary logging to be enabled through the cluster parameter group; once on, changes can be captured without querying production tables. Azure SQL Database: It speaks the same TDS protocol as on-premises SQL Server, so existing SQL Server drivers and tools connect without modification. Stacksync's field mapping accounts for these differences between AWS Aurora MySQL and Azure SQL Database without custom code.
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 MySQL and Azure SQL Database.