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Security and identity ⇄ Database

Active Directory to AWS Aurora MySQL integration — real-time, two-way sync

Keep Active Directory and AWS Aurora MySQL 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 Active Directory and AWS Aurora MySQL

Close the gap between your application data and your directory: AWS Aurora MySQL and Active Directory share users, groups, and access in real time, in both directions.

Active Directory is the system of record for who people are and what they can reach: users, the groups they belong to, and the applications assigned to them. AWS Aurora MySQL holds the operational data those same people show up in, whether an employee or member table that decides who should have an account at all, a customers list, or the rows an application checks before it authorizes an action. The two describe overlapping users and groups, and when a nightly export or a hand-run script is all that connects them, accounts lag joiners and leavers and the application authorizes against a stale picture of who has access.

Stacksync syncs Views, Foreign keys, Stored procedures and triggers, Databases (schemas) in AWS Aurora MySQL with Organizational units, Organizational contacts, Users, Groups in Active Directory field by field, in real time, and in both directions. You decide which system owns which fields, with the directory holding credentials and group membership and the database holding the source list of people who should exist at all, and Stacksync keeps every copy consistent, resolving conflicts by rules you set. A person added to a table becomes an account within seconds, a departure disables one just as fast, and the directory's users and groups are always present in your tables as ordinary rows.

Common use cases

  • 01 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
  • 02 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
  • 03 Read Users, Groups, and directoryRole assignments into a warehouse for periodic access reviews and SOC 2 audit evidence.
  • 04 Keep security-group memberships aligned with application entitlement tables so access reflects the right teams as they change.

Common sync patterns

Read users and groups as ordinary tables

Users, groups, and their memberships from Active Directory land in AWS Aurora MySQL as rows your application and queries can join, so authorization checks and access reporting run against the database instead of the directory API.

Keep group and role membership aligned

A group or role change made in either system updates the other, so the entitlements an application enforces match what the directory grants.

One profile, kept current

A name, department, email, or manager corrected in either system updates the other, so the profile the directory shows and the data the application reads stop drifting apart.

What you can sync between Active Directory and AWS Aurora MySQL

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.

Active Directory objects AWS Aurora MySQL objects How this pairing syncs
Service principals & applications App registrations and enterprise apps; read-mostly for entitlement and license inventory. Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Service principals & applications is specific to Active Directory and Rows to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Organizational units On-prem AD DS containers (LDAP organizationalUnit) used to scope which users and groups a sync includes. Columns MySQL data types are mapped to the paired system's field types during schema setup. Organizational units is specific to Active Directory and Columns to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Organizational contacts Directory contact objects (orgContact); synced for shared address-book and CRM person records. Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Organizational contacts is specific to Active Directory and Primary keys and indexes to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Users User accounts in Entra ID and on-prem AD DS; synced two-way to create, update attributes, and enable or disable accounts. Views Can serve as read-only sync sources for derived or filtered datasets. Users is specific to Active Directory and Views to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Groups Security and Microsoft 365 groups; synced two-way including name, type, and owner, with membership tracked separately. Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Groups is specific to Active Directory and Foreign keys to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Group memberships Member and owner links between users and groups; membership add/remove changes are surfaced by delta query. Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Group memberships is specific to Active Directory and Stored procedures and triggers to AWS Aurora MySQL — each maps to any object or custom field on the other side.

How changes propagate between Active Directory and AWS Aurora MySQL

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.

Active Directory AWS Aurora MySQL Sub-second propagation

DetectionActive Directory notifies Stacksync of record changes through webhook events. Microsoft Graph delta query (change tracking) for Users and Groups, plus change-notification subscriptions (webhooks) for near-real-time triggers.

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

AWS Aurora MySQL Active Directory 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 written to Active Directory through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Active Directory: Graph throttles by resource-unit cost per app per tenant in 10-second windows (about 3,500–8,000 units by tenant size); directory delta tokens expire after ~7 days.
What ships with Active Directory ⇄ AWS Aurora MySQL

Connect Active Directory and AWS Aurora MySQL for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Active Directory or AWS Aurora MySQL 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 Active Directory or AWS Aurora MySQL record.

Observability

Monitoring

Track your Active Directory ⇄ AWS Aurora MySQL sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Active Directory and AWS Aurora MySQL.

How the Active Directory and AWS Aurora MySQL connectors work

Active Directory

Integration surface
Microsoft Graph REST API (Entra ID / cloud) and LDAP/LDAPS (on-premises AD DS)
Authentication
OAuth 2.0 via the Microsoft identity platform — an app registration with application or delegated permissions (e.g. User.ReadWrite.All, Group.ReadWrite.All) and admin consent; on-prem AD DS uses a bound service account over LDAPS.
Change detection
Microsoft Graph delta query (change tracking) for Users and Groups, plus change-notification subscriptions (webhooks) for near-real-time triggers; on-prem AD DS uses the DirSync control and uSNChanged polling.
Capabilities
read · write · webhooks
Rate limits
Graph throttles by resource-unit cost per app per tenant in 10-second windows (about 3,500–8,000 units by tenant size); directory delta tokens expire after ~7 days.

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
How it works

How to connect Active Directory to AWS Aurora MySQL — 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 Active Directory and AWS Aurora MySQL 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
    Active Directory connected
    AWS Aurora MySQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Active Directory and AWS Aurora MySQL 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 · Active Directory ⇄ AWS Aurora MySQL
    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
    Active Directory AWS Aurora MySQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Active Directory and AWS Aurora MySQL 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.

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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 448 integrations available for Active Directory and AWS Aurora MySQL.

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