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Data warehouse ⇄ Business productivity

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

Keep Databricks and Microsoft Teams 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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Why teams connect Databricks and Microsoft Teams

Get the data locked inside Microsoft Teams into Databricks as live tables, and send results back where Microsoft Teams can use them, without writing a pipeline.

Whatever Microsoft Teams is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.

Stacksync syncs Online Meetings, Tabs & Installed Apps, Teams, Channels from Microsoft Teams into tables in Databricks continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Databricks can also be written back into fields in Microsoft Teams where the tool can use them.

Common use cases

  • Notify an ops channel when a sync detects failed or conflicting records that need review.
  • Sync team membership from HR or identity systems so channels match the org chart.
  • Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.

Where Microsoft Teams accepts updates: operational write-back

Segments, scores, or reference values computed in Databricks sync back onto records in Microsoft Teams, putting analysis where the work happens.

History that outlives the tool

A continuously synced copy in Databricks preserves a queryable record even as data ages out of Microsoft Teams or gets changed inside it.

Analytics on Microsoft Teams's data

Records and events from Microsoft Teams land in Databricks as queryable tables, current within seconds and ready to join with the rest of the warehouse.

What you can sync between Databricks and Microsoft Teams

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 Teams objects
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Channels Channel targets used for routing synced notifications and updates.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Channel Messages Posted messages read for archiving or written to broadcast record changes.
Views Curated read-only projections used as sync sources for downstream tools. Chats & Chat Messages 1:1 and group chat content read under protected-API access for compliance use.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Team Members & Users Membership synced with identity, HR, or CRM ownership data.
Volumes Unity Catalog file storage used for staging bulk loads. Online Meetings Meeting records synced with scheduling and CRM activity timelines.
SQL Warehouses The compute endpoint a sync connects to for query execution. Tabs & Installed Apps App configuration read to audit or provision team workspaces.
What ships with Databricks ⇄ Microsoft Teams

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Microsoft Teams 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 Teams record.

Observability

Monitoring

Track your Databricks ⇄ Microsoft Teams 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 Teams.

How the Databricks and Microsoft Teams 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 Teams

Integration surface
REST API (Microsoft Graph)
Authentication
OAuth 2.0 via Microsoft Entra ID; reading message content at scale requires Microsoft-approved protected-API access
Change detection
Graph change notifications (webhooks) for messages and membership; delta queries on some resources
Capabilities
read · write · webhooks
How it works

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

    Choose tables

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

Databricks and Microsoft Teams integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for Databricks and Microsoft Teams.

Popular · 8 of 386
All Databricks integrations All Microsoft Teams integrations Browse all integrations
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