Gong to Databricks integration
Connect Gong to Databricks and automatically sync your CRM data. Weld extracts data from Gong, loads it into Databricks, and lets you transform the data using SQL or dbt, no custom scripts required.
Source
WarehouseSourceGongConnected- user20 cols
- workspace4 cols
- call29 cols
- library_folder7 cols
- answered_scorecard10 cols
- call_in_folder10 cols
- Extract
- Load
- Keep in sync
DestinationDatabricksReady- gong.userSynced
- gong.workspaceSyncing
- gong.callSynced
- gong.library_folderSynced
- gong.answered_scorecardSynced
- gong.call_in_folderSynced
- Gong tables
- 63
- fields, typed
- 481
- relationships kept
- 35
- agent context included
- MCP
Trusted by data and AI teams
Why sync Gong to Databricks?
Ready for analysis.
Centralizing your Gong data in Databricks lets you join it with other data sources for cross-platform analytics and deeper insights.
Build reliable dashboards and reports by querying Gong data directly in Databricks using SQL or your preferred BI tool.
Combine Gong data with other customer touchpoints to build a unified customer view across sales, marketing, and support.
Sales pipeline analytics
Analyze your full sales funnel in Databricks. Join CRM data with marketing and product data for complete attribution.
Centralized data warehouse
Bring Gong data into Databricks alongside other sources to create a single source of truth for your organization.
Automated reporting
Replace manual exports and spreadsheet-based reporting with automated pipelines from Gong to Databricks. Connect BI tools like Looker, Metabase, or Power BI.
What data can you sync?
Every Gong table, keys intact.
Weld syncs the objects the Gong connector exposes into Databricks, and you choose which tables and fields to include. The connector's docs list what is available.
- user
- workspace
- call
- library_folder
- answered_scorecard
- call_in_folder
- scorecard
- manual_call_integration
- manual_call
- permission_profile
- tracker
- call_participant
- call_context_integration
- call_outline
- call_outline_item
- call_highlight_item_start_time
- transcript_sentence
- call_speaker
- call_highlight_item
- call_highlight
- call_key_point
- transcript
- user_setting_history
- permission_call_access
- permission_coaching_access
- permission_deal_access
- permission_email_access
- permission_forecast_access
- permission_forecast_edit_submission_access
- permission_forecast_edit_target_access
- and 33 more
Ask your agent.
It queries Databricks for you.
Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Gong context, finds the tables it needs and runs the query in Databricks.
How many call rows do we have per workspace? Use our Gong data in Databricks.
Reading the Gong context first, so the query uses the right tables and keys.
Technical considerations.
What to expect.
- Incremental syncing
- Weld uses incremental syncing where supported by the Gong API, loading only new and updated records to minimize data transfer and warehouse costs.
- Schema handling
- Weld automatically manages schema changes. If Gong adds new fields, they're detected and added to the corresponding Databricks tables.
- Data freshness
- Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
- Security
- All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.
Keep reading.
Guides, docs and schema.
Common questions.
About Gong to Databricks.
Start syncing Gong to Databricks.
Set up your Gong data pipeline in minutes. No credit card required. Free for 14 days.
SourceWarehouse
