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Data warehouse ⇄ Developer tools

Databricks to Microsoft Graph integration — real-time, two-way sync

Keep Databricks and Microsoft Graph 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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Why teams connect Databricks and Microsoft Graph

Close the gap between analytics and operations: Databricks holds the record while Microsoft Graph runs the day-to-day work, and Stacksync keeps the two in step in real time, in both directions.

Databricks is the central store where teams keep Change Data Feed, Catalogs, Schemas, Delta Tables for reporting and analysis; Microsoft Graph runs the operational side of engineering work — tracking issues, moving messages and events, watching systems, and managing users and access. The two overlap wherever the same operational data matters to both: the Calendar events, Contacts, Drive items (OneDrive & SharePoint), Teams messages and chats produced in Microsoft Graph are exactly what analysts want to measure in Databricks, and the curated rows in Databricks are what should drive the next action in Microsoft Graph. When that overlap is bridged by nightly ETL or hand-written scripts, dashboards lag a day behind reality and the tools that should react to warehouse signals never see them.

Stacksync syncs Change Data Feed, Catalogs, Schemas, Delta Tables in Databricks with Calendar events, Contacts, Drive items (OneDrive & SharePoint), Teams messages and chats in Microsoft Graph field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync matches records on a stable external key, keeps every copy consistent, and resolves conflicts by rules you set — so analytics and operations work from the same current data instead of two drifting copies.

Common use cases

  • 01 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • 02 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 03 Sync Outlook Calendar events and Contacts two-way with a CRM so reps' meetings and the people they meet stay aligned across both systems.
  • 04 Send Outlook mail through the sendMail action when a database or CRM record changes, then read replies back onto the same record.

Common sync patterns

Warehouse signals reach Microsoft Graph

A row scored, flagged, or enriched in Databricks creates or updates the matching record in Microsoft Graph, so the operational tool acts on the same data the analysts already see.

Backfill history, then stay live

Load the existing set of Calendar events, Contacts, Drive items (OneDrive & SharePoint), Teams messages and chats into Databricks once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.

No batch jobs to babysit

New and changed records move field by field the moment they change, replacing scheduled ETL and one-off scripts that fail quietly and leave stale rows behind.

What you can sync between Databricks and Microsoft Graph

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.

Databricks objects Microsoft Graph objects How this pairing syncs
SQL Warehouses The compute endpoint a sync connects to for query execution. Calendar events Outlook events via /users/{id}/events; read and write meetings, attendees, and recurrence, and accept or decline invitations. SQL Warehouses is specific to Databricks and Calendar events to Microsoft Graph — each maps to any object or custom field on the other side.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Contacts Personal Outlook contacts via /users/{id}/contacts; full create, read, update, delete, synced two-way with CRM person records. Change Data Feed is specific to Databricks and Contacts to Microsoft Graph — each maps to any object or custom field on the other side.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Drive items (OneDrive & SharePoint) Files and folders via /drives and /me/drive; read and write items, upload and download content, and read per-item metadata. Catalogs is specific to Databricks and Drive items (OneDrive & SharePoint) to Microsoft Graph — each maps to any object or custom field on the other side.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Teams messages and chats Channel messages and chats via /teams/{id}/channels and /chats; read message history and post new messages for alerts and archiving. Schemas is specific to Databricks and Teams messages and chats to Microsoft Graph — each maps to any object or custom field on the other side.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Planner tasks Plans, buckets, and tasks via /planner; read and write task status, assignments, and due dates to keep project state in sync. Delta Tables is specific to Databricks and Planner tasks to Microsoft Graph — each maps to any object or custom field on the other side.
Views Curated read-only projections used as sync sources for downstream tools. Users Entra ID user accounts read and written via /users; create, update profile attributes, and enable or disable accounts with User.ReadWrite.All. Views is specific to Databricks and Users to Microsoft Graph — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Microsoft Graph

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.

Databricks Microsoft Graph 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 Microsoft Graph through its API, with automatic retries and rate-limit backoff.

Microsoft Graph Databricks Sub-second propagation

DetectionMicrosoft Graph notifies Stacksync of record changes through webhook events. Delta query (change tracking) returns created, updated, and deleted items since the last deltaLink for users, groups, mail, events, contacts, and.

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

Rate-limit considerations

  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
  • Microsoft Graph: Throttled per app and per tenant, returning HTTP 429 with a Retry-After header; limits vary by service — the Outlook mail service allows about 10,000 requests per 10 minutes per app per mailbox with up to 4 concurrent requests, and delta and subscription tokens expire and must be renewed.
What ships with Databricks ⇄ Microsoft Graph

Connect Databricks and Microsoft Graph for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Microsoft Graph connection.

Real-time

Two-way sync

Changes in Databricks or Microsoft Graph instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Microsoft Graph 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 Databricks or Microsoft Graph record.

Observability

Monitoring

Track your Databricks ⇄ Microsoft Graph sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and Microsoft Graph.

How the Databricks and Microsoft Graph connectors work

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

Microsoft Graph

Integration surface
Microsoft Graph unified REST API (v1.0 and beta) at graph.microsoft.com, spanning Microsoft 365 services — Entra ID, Outlook mail and calendar, OneDrive and SharePoint, Teams, and Planner; supports JSON $batch (up to 20 requests per call).
Authentication
OAuth 2.0 via the Microsoft identity platform (Microsoft Entra ID). An app registration holds delegated or application (app-only) scopes such as Mail.ReadWrite, Calendars.ReadWrite, Files.ReadWrite.All, User.ReadWrite.All, and Group.ReadWrite.All; application permissions require tenant admin consent.
Change detection
Delta query (change tracking) returns created, updated, and deleted items since the last deltaLink for users, groups, mail, events, contacts, and driveItems; change-notification subscriptions (webhooks) POST near-real-time notifications to a notification URL and must be renewed before they expire.
Capabilities
read · write · webhooks
Rate limits
Throttled per app and per tenant, returning HTTP 429 with a Retry-After header; limits vary by service — the Outlook mail service allows about 10,000 requests per 10 minutes per app per mailbox with up to 4 concurrent requests, and delta and subscription tokens expire and must be renewed.
How it works

How to connect Databricks to Microsoft Graph — 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 Databricks and Microsoft Graph 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
    Databricks connected
    Microsoft Graph connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and Microsoft Graph 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 · Databricks ⇄ Microsoft Graph
    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
    Databricks Microsoft Graph
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Microsoft Graph 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 362 integrations available for Databricks and Microsoft Graph.

Popular · 5 of 362
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