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Data warehouse ⇄ CRM

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

Keep Databricks and Gong 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 Gong

Sync Gong into Databricks continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. CRM Objects, Library, Data Privacy (Erasure), Calls from Gong land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Gong. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Sync Interaction Stats such as talk ratios and per-rep activity into a coaching database for engagement and rep-performance dashboards.
  • 02 Import externally recorded dialer or web-conference calls into Gong via POST /v2/calls so they get transcribed and analyzed like native Gong calls.
  • 03 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • 04 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.

Common sync patterns

Cleanup that sticks

Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.

CRM analytics on live data

Accounts, contacts, and activity from Gong are queryable in Databricks moments after they change, so dashboards stop lagging the reality they describe.

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Databricks appear as fields in Gong, where the people working accounts actually see them.

What you can sync between Databricks and Gong

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 Gong objects How this pairing syncs
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Calls Retrieved via POST /v2/calls/extensive with participants, topics, trackers, scorecards, and media URLs, filtered by fromDateTime/toDateTime; external recordings are also imported via POST /v2/calls with media uploaded via PUT /v2/calls/{id}/media. Read and write. Schemas is specific to Databricks and Calls to Gong — 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. Transcripts Speaker-attributed, timestamped sentences retrieved via POST /v2/calls/transcript for one or more callIds; available only after asynchronous processing completes. Read-only. Delta Tables is specific to Databricks and Transcripts to Gong — 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 Gong users and team members with roles, titles, email, and settings, read via GET /v2/users to map call owners and participants to CRM and warehouse identities. Read-only. Views is specific to Databricks and Users to Gong — each maps to any object or custom field on the other side.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Interaction Stats (Activity) Aggregated talk/listen ratios, interaction stats, and day-by-day user activity retrieved via POST /v2/stats endpoints; read out for coaching and engagement reporting. Read-only. Materialized Views is specific to Databricks and Interaction Stats (Activity) to Gong — each maps to any object or custom field on the other side.
Volumes Unity Catalog file storage used for staging bulk loads. Trackers & Scorecards Keyword and topic tracker definitions plus coaching scorecards, including answered scorecards, read from Settings as coaching and deal-risk signals. Read-only. Volumes is specific to Databricks and Trackers & Scorecards to Gong — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. CRM Objects Accounts, opportunities, stages, and users uploaded into Gong through the CRM integration API so CRM context appears alongside conversations. Write (upload) path. SQL Warehouses is specific to Databricks and CRM Objects to Gong — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Gong

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

Gong Databricks Interval-based propagation

DetectionStacksync polls Gong for changes on an incremental schedule, reading only records changed since the previous pass. Polling POST /v2/calls/extensive on fromDateTime/toDateTime.

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.
  • Gong: 3 API calls per second and 10,000 calls per day per company by default; exceeding returns HTTP 429 with a Retry-After header, and limits can be raised by contacting Gong.
What ships with Databricks ⇄ Gong

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Gong 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 Gong record.

Observability

Monitoring

Track your Databricks ⇄ Gong 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 Gong.

How the Databricks and Gong 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

Gong

Integration surface
REST API on api.gong.io/v2 - retrieval endpoints (calls, transcript, users, stats, settings, library, logs) plus write endpoints for importing calls, uploading CRM data, and data-privacy erasure
Authentication
Basic authorization header combining an Access Key and Access Key Secret (created by a Gong technical admin, base64-encoded as key:secret); OAuth 2.0 Bearer tokens are supported for marketplace apps
Change detection
Polling POST /v2/calls/extensive on fromDateTime/toDateTime; the public API exposes no outbound webhooks or CDC, though a Gong admin can configure a product-side automation Rule that POSTs matching calls to a URL. Transcripts and analysis appear only after asynchronous processing.
Capabilities
read · write
Rate limits
3 API calls per second and 10,000 calls per day per company by default; exceeding returns HTTP 429 with a Retry-After header, and limits can be raised by contacting Gong.
Gong setup guide
How it works

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

    Choose tables

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

Databricks and Gong 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 573 integrations available for Databricks and Gong.

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