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Data warehouse ⇄ Communications

Databricks to Zoom integration — real-time, two-way sync

Keep Databricks and Zoom 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 Databricks and Zoom

Land the messages, calls, and events from Zoom in Databricks as live tables, and write results back, without building or maintaining a pipeline.

Zoom produces a constant stream of activity — messages sent and received, calls placed and answered, meetings held, and the delivery and engagement events attached to them. That record is what the rest of the company wants to analyze, and it usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay to get it out.

Stacksync syncs Registrants, Cloud Recordings, Participant Reports, Zoom Phone Call Logs from Zoom into tables in Databricks in real time, handling schema, rate limits, and retries. Because the connection works in both directions, results computed in Databricks — segments, contact updates, suppression flags — can be written back into fields in Zoom wherever it exposes them, so analysis lands where outreach actually happens.

Common use cases

  • 01 Land Cloud Recording metadata and past-meeting Participant Reports into a warehouse for compliance archival and usage analytics.
  • 02 Push Zoom Phone call logs into an operational database so sales and support calls are logged against the right customer records.
  • 03 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 04 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.

Common sync patterns

Communications analytics without ETL

Messages, calls, and events from Zoom arrive in Databricks as queryable tables, current within seconds instead of a day behind.

Engagement and delivery on live data

Sends, opens, clicks, bounces, and call outcomes from Zoom land in Databricks as they happen, so deliverability and response monitoring stop lagging the reality they describe.

Activity joined with everything else

Combine Zoom's activity with the CRM, product, and support data already in Databricks to attribute outcomes to the touches that drove them, which no single tool can do alone.

What you can sync between Databricks and Zoom

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 Zoom objects How this pairing syncs
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Zoom Phone Call Logs Call detail records and recordings from Zoom Phone (requires the Phone license); read into a database to log calls against customers. Materialized Views is specific to Databricks and Zoom Phone Call Logs to Zoom — each maps to any object or custom field on the other side.
Volumes Unity Catalog file storage used for staging bulk loads. Team Chat Channels and Messages Chat channels, membership, and messages; listed and sent two-way to align collaboration spaces with team data. Volumes is specific to Databricks and Team Chat Channels and Messages to Zoom — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. Users Account members with license type, role, and status; created, updated, and deactivated two-way to sync with HRIS or identity systems. SQL Warehouses is specific to Databricks and Users to Zoom — 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. Groups User groups that carry policy and settings; membership synced from department or team data in an operational database. Change Data Feed is specific to Databricks and Groups to Zoom — 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. Meetings Scheduled and instant meetings with join URLs and settings; created and updated from a CRM or calendar, read back for reporting. Catalogs is specific to Databricks and Meetings to Zoom — 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. Webinars Webinar events (requires the Webinar license); created and managed via API, with panelists and settings written from event tools. Schemas is specific to Databricks and Webinars to Zoom — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Zoom

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 Zoom 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 Zoom through its API, with automatic retries and rate-limit backoff.

Zoom Databricks Sub-second propagation

DetectionZoom notifies Stacksync of record changes through webhook events. Webhooks via Event Subscriptions (meeting.started/ended, participant joined/left, user.created/updated, recording.completed, and more) for real-time.

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.
  • Zoom: APIs are grouped into Light, Medium, Heavy, and Resource-intensive categories with per-second and daily quotas that scale by plan (e.g. Business+ Heavy APIs allow 40/second within a 60,000/day combined cap); exceeding a limit returns HTTP 429.
What ships with Databricks ⇄ Zoom

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Zoom 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 Zoom record.

Observability

Monitoring

Track your Databricks ⇄ Zoom 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 Zoom.

How the Databricks and Zoom 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

Zoom

Integration surface
REST API (v2) with webhook Event Subscriptions
Authentication
OAuth 2.0 — user-authorized OAuth or Server-to-Server OAuth using account credentials; access tokens are valid for one hour and requests use granular per-resource scopes (e.g. meeting:read, user:write)
Change detection
Webhooks via Event Subscriptions (meeting.started/ended, participant joined/left, user.created/updated, recording.completed, and more) for real-time events, with polling on list endpoints using date-range filters for backfill and objects without an event
Capabilities
read · write · webhooks
Rate limits
APIs are grouped into Light, Medium, Heavy, and Resource-intensive categories with per-second and daily quotas that scale by plan (e.g. Business+ Heavy APIs allow 40/second within a 60,000/day combined cap); exceeding a limit returns HTTP 429.
How it works

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

    Choose tables

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

Databricks and Zoom 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 454 integrations available for Databricks and Zoom.

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