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Go HighLevel to Databricks integration

Connect Go HighLevel to Databricks and automatically sync your CRM data. Weld extracts data from Go HighLevel, loads it into Databricks, and lets you transform the data using SQL or dbt, no custom scripts required.

Start for freeView setup guide
4.8 on G2
Go HighLevelSource
WeldWeld
DatabricksWarehouse
Weld · New sync
Go HighLevelSourceGo HighLevelConnected
Tables to sync
  • contact118 cols
  • order48 cols
  • opportunity37 cols
  • transaction72 cols
  • subscription64 cols
  • message27 cols
  • Extract
  • Load
  • Keep in sync
DatabricksDestinationDatabricksReady
go_high schema
  • go_high.contactSynced
  • go_high.orderSyncing
  • go_high.opportunitySynced
  • go_high.transactionSynced
  • go_high.subscriptionSynced
  • go_high.messageSynced
Go HighLevel tables
36
fields, typed
806
relationships kept
18
agent context included
MCP

Trusted by data and AI teams

  • Flatpay
  • Holafly
  • eComplete
  • Dishoom
  • Danish Endurance
  • Female Invest
  • Son of a Tailor
  • Onomondo
  • Medik8
  • Pas Normal Studios
How it works

How to set up Go HighLevel to Databricks in Weld.
In the app, with the API or an agent.

Setup guideAPI guideMCP docs
Weld · New Go HighLevel sync
Go HighLevelNew connectionGo HighLevelAuthorised
Connection namego_high
AuthorizeOpens Go HighLevel to grant read access
Use cases

Why sync Go HighLevel to Databricks?
Ready for analysis.

Centralizing your Go HighLevel 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 Go HighLevel data directly in Databricks using SQL or your preferred BI tool.

Combine Go HighLevel 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 Go HighLevel 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 Go HighLevel to Databricks. Connect BI tools like Looker, Metabase, or Power BI.

Schema

What data can you sync?
Every Go HighLevel table, keys intact.

Weld syncs the objects the Go HighLevel connector exposes into Databricks, and you choose which tables and fields to include. The connector's docs list what is available.

Open the schema explorer
All 36 tables
  • contact
  • order
  • opportunity
  • transaction
  • subscription
  • message
  • conversation
  • pipeline
  • pipeline_stage
  • contact_opportunities
  • fulfillment_items
  • form_submission
  • fulfillment
  • fulfillment_item_price_membership_offers
  • fulfillment_trackings
  • fulfillment_item_product_variants
  • invoice
  • invoice_items
  • invoice_reminders
  • opportunity_relations
  • fulfillment_item_product_variant_options
  • opportunity_custom_fields
  • contact_additional_emails
  • invoice_late_fees_configuration_meta
  • contact_custom_fields
  • contact_tags
  • contact_additional_phones
  • contact_followers
  • form_submission_others
  • opportunity_notes
  • and 4 more
Weld MCP server

Ask your agent.
It queries Databricks for you.

Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Go HighLevel context, finds the tables it needs and runs the query in Databricks.

Set up the MCP serverClaudeCursorChatGPTGemini
Claude CodeOpus 5
>

How many order rows do we have per contact? Use our Go HighLevel data in Databricks.

Reading the Go HighLevel context first, so the query uses the right tables and keys.

●weld·search_available_references
⎿raw.go_high.order
raw.go_high.contact
+ 34 more Go HighLevel tables
●weld·get_reference_schema
⎿order · 48 columns
joins contact on contact_id
●weld·run_query
⎿select c.id, count(*) from {{raw.go_high.order}} o
join {{raw.go_high.contact}} c on o.contact_id = c.id
group by 1
submitted
●weld·get_query_status
⎿DONE
●weld·get_query_result
⎿rows returned
✓Answered from Go HighLevel data in Databricks
>Ask about your Go HighLevel data
Under the hood

Technical considerations.
What to expect.

Incremental syncing
Weld uses incremental syncing where supported by the Go HighLevel API, loading only new and updated records to minimize data transfer and warehouse costs.
Schema handling
Weld automatically manages schema changes. If Go HighLevel 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.
Resources

Keep reading.
Guides, docs and schema.

Documentation

Go HighLevel setup guide

How to connect Go HighLevel to Weld, step by step.

Documentation

Databricks setup guide

How to connect Databricks to Weld, step by step.

Schema

Go HighLevel schema explorer

Browse all 36 tables and 806 fields.

Connector

Go HighLevel connector

Everything Weld does with Go HighLevel.

FAQ

Common questions.
About Go HighLevel to Databricks.

Start syncing Go HighLevel to Databricks.

Set up your Go HighLevel data pipeline in minutes. No credit card required. Free for 14 days.

Go HighLevelSource
WeldWeld
DatabricksWarehouse
Start for freeTalk to us
Related

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