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AWS Aurora MySQL to SQL Server integration — real-time, two-way sync

Keep AWS Aurora MySQL and SQL Server 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 AWS Aurora MySQL and SQL Server

Keep AWS Aurora MySQL and SQL Server synchronized in real time, across engines, regions, or services, in one or both directions.

Teams sync AWS Aurora MySQL with SQL Server when applications span both engines — for example a cloud application on Aurora and legacy or departmental systems on SQL Server. The sync maps Aurora MySQL Tables, Columns, and Primary keys and indexes to SQL Server Tables, Columns, and Primary and Unique Keys so both databases hold consistent records.

Stacksync syncs tables or collections between AWS Aurora MySQL and SQL Server 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 Keep a SQL Server reporting or legacy environment current with a cloud application running on Aurora MySQL.
  • 02 Migrate from SQL Server to Aurora MySQL (or the reverse) with both databases live during the transition.
  • 03 Serve Aurora MySQL data to downstream tools that read from SQL Server Views.
  • 04 Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.

Common sync patterns

Cross-engine table replication

Aurora MySQL Tables and Rows sync into SQL Server Tables under a designated Schema, matched on primary keys.

Two-way record consistency

updates to records in either Aurora MySQL or SQL Server propagate to the other side, keyed on Primary and Unique Keys.

Schema alignment

Column additions in Aurora MySQL Tables are reflected in the corresponding SQL Server Tables.

What you can sync between AWS Aurora MySQL and SQL Server

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 SQL Server objects How this pairing syncs
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 to records in connected systems. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Columns Field-level mapping targets with T-SQL types. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Can serve as read-only sync sources for derived or filtered datasets. Views Read-side projections used as outbound sync sources. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Stored Procedures T-SQL logic that can validate or post-process synced rows. Foreign keys is specific to AWS Aurora MySQL and Stored Procedures to SQL Server — each maps to any object or custom field on the other side.
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Databases Instance-level databases that scope a sync's reads and writes. Stored procedures and triggers is specific to AWS Aurora MySQL and Databases to SQL Server — each maps to any object or custom field on the other side.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Schemas Namespaces (dbo and custom) used to organize synced tables. Databases (schemas) is specific to AWS Aurora MySQL and Schemas to SQL Server — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL and SQL Server

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 MySQL SQL Server Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

DeliveryEach detected change is applied to SQL Server as a row-level write, with types converted between the two schemas.

SQL Server AWS Aurora MySQL Sub-second propagation

DetectionChanges in SQL Server are captured at the source via change data capture — no polling loop against its API. SQL Server Native Change Data Capture (CDC).

DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • SQL Server: No API rate limits; throughput depends on instance resources, licensing tier, and connection limits.
What ships with AWS Aurora MySQL ⇄ SQL Server

Connect AWS Aurora MySQL and SQL Server for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–SQL Server connection.

Real-time

Two-way sync

Changes in AWS Aurora MySQL or SQL Server instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora MySQL or SQL Server 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 MySQL or SQL Server record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ SQL Server 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 MySQL and SQL Server.

How the AWS Aurora MySQL and SQL Server connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
Capabilities
read · write · CDC

SQL Server

Integration surface
SQL over the TDS wire protocol (Tabular Data Stream), via ODBC/JDBC/ADO.NET drivers
Authentication
Database credentials entered as a connection string or as parameters (host/user/password) in the Create New Sync page
Change detection
SQL Server Native Change Data Capture (CDC); a DBA runs a one-time setup script with sysadmin privileges to enable CDC and create Stacksync wrapper procedures
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance resources, licensing tier, and connection limits
SQL Server setup guide
How it works

How to connect AWS Aurora MySQL to SQL Server — 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.

  1. 01

    Connect your apps

    Authenticate AWS Aurora MySQL and SQL Server with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    AWS Aurora MySQL connected
    SQL Server connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL and SQL Server 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · AWS Aurora MySQL ⇄ SQL Server
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    AWS Aurora MySQL SQL Server
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL and SQL Server integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 483 integrations available for AWS Aurora MySQL and SQL Server.

Popular · 7 of 483
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