Real-time
Two-way sync
Changes in Active Directory or Databricks instantly reflect in both systems. No stale data, no manual imports.
Security and identity ⇄ Data warehouse
Active Directory to Databricks integration — real-time, two-way sync
Keep Active Directory and Databricks 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
Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from Celigo
Why teams connect Active Directory and Databricks
Land the users, groups, and access events from Active Directory in Databricks continuously for security analytics, and write computed results back — without building or maintaining a pipeline.
Active Directory is the record of who exists and what they can reach; Databricks is where the business measures everything else. The two overlap on people and their access — the same users, groups, roles, and events that Active Directory governs are what security, compliance, and analytics teams want to query in Databricks. Getting them there usually means a brittle export that runs overnight and hands auditors a snapshot that is already out of date.
Stacksync syncs Service principals & applications, Organizational units, Organizational contacts, Users from Active Directory into tables in Databricks in real time, and the connection works in both directions: values computed in Databricks, such as risk scores or access-review decisions, can be written back to attributes in Active Directory where the identity team acts on them. Schema changes are handled, API limits are managed, and the sync is something you configure rather than a pipeline you keep alive.
Common use cases
- 01 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
- 02 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- 03 Keep security-group memberships aligned with application entitlement tables so access reflects the right teams as they change.
- 04 Read Devices and service principals into a database for identity, asset, and license inventory across the tenant.
Common sync patterns
Directory data in the warehouse, minus the pipeline
Users, groups, and roles from Active Directory arrive in Databricks as queryable tables, current within seconds instead of a nightly directory export.
Access and sign-in analytics
Sign-in and access events from Active Directory land in Databricks, so security and compliance teams can query who reached what, and when, alongside the rest of the business's data.
Access governance on joined data
Join Active Directory's users and group memberships with HR, product, and usage data already in Databricks to surface who holds access they no longer need.
What you can sync between Active Directory and Databricks
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 | Databricks objects | How this pairing syncs | |
|---|---|---|---|
| Groups Security and Microsoft 365 groups; synced two-way including name, type, and owner, with membership tracked separately. | Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Groups is specific to Active Directory and Materialized Views to Databricks — 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. | Volumes Unity Catalog file storage used for staging bulk loads. | Group memberships is specific to Active Directory and Volumes to Databricks — each maps to any object or custom field on the other side. | |
| Devices Registered and joined device objects; typically read into a database for inventory and compliance reporting. | SQL Warehouses The compute endpoint a sync connects to for query execution. | Devices is specific to Active Directory and SQL Warehouses to Databricks — each maps to any object or custom field on the other side. | |
| Directory roles Admin role assignments (directoryRole); read for access reviews and least-privilege governance. | Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Directory roles is specific to Active Directory and Change Data Feed to Databricks — each maps to any object or custom field on the other side. | |
| Service principals & applications App registrations and enterprise apps; read-mostly for entitlement and license inventory. | Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Service principals & applications is specific to Active Directory and Catalogs to Databricks — 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. | Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Organizational units is specific to Active Directory and Schemas to Databricks — each maps to any object or custom field on the other side. |
How changes propagate between Active Directory and Databricks
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 Databricks 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 Databricks as a row-level write, with types converted between the two schemas.
Databricks Active Directory Sub-second propagation
DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.
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.
- Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Active Directory ⇄ Databricks
Connect Active Directory and Databricks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Active Directory–Databricks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Active Directory or Databricks 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 Databricks record.
Observability
Monitoring
Track your Active Directory ⇄ Databricks 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 Databricks.
How the Active Directory and Databricks 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.
Databricks
- Integration surface
- SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
- Authentication
- Personal access tokens or OAuth machine-to-machine credentials for service principals
- Change detection
- Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
- Capabilities
- read · write · CDC
- Rate limits
- Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
How it works
How to connect Active Directory to Databricks — 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 Active Directory and Databricks with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Active Directory
connected
Databricks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Active Directory and Databricks 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 · Active Directory ⇄ DatabricksCustomers 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.
Active Directory DatabricksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Active Directory and Databricks integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Active Directory and Databricks: authenticate both systems, choose the objects to sync (such as Active Directory's Groups and Group memberships), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Active Directory and Databricks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Active Directory–Databricks integration in-house.
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Yes — Stacksync ships production-grade connectors for both Active Directory and Databricks. 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 Active Directory: 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. On Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. 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 Databricks side: Catalogs, Schemas, Delta Tables, Views, plus custom fields where Databricks exposes them. On the Active Directory side: Service principals & applications, Organizational units, Organizational contacts, Users. 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.
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 548 integrations available for Active Directory and Databricks.
Popular · 8 of 548
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Active Directory ⇄ Starburst Enterprise -
Active Directory ⇄ StarRocks -
Active Directory ⇄ Teradata Vantage -
Active Directory ⇄ Tinybird -
Databricks ⇄ Onelogin -
Databricks ⇄ Auth0 -
Databricks ⇄ Jumpcloud - Databricks ⇄ Azure Active Directory
No integrations match .
