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CRM ⇄ Data warehouse

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

Keep Close and Databricks 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 Close and Databricks

Sync Close 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. Contacts, Opportunities, Activities, Tasks from Close land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Close. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Write product usage or firmographic data from an internal database onto Close lead custom fields to prioritize follow-up.
  • Sync Close leads and opportunities into Postgres or a warehouse for pipeline reporting outside Close's built-in reports.
  • Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • Serve ML feature outputs computed in Databricks to production apps through a synced operational store.

CRM analytics on live data

Accounts, contacts, and activity from Close 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 Close, where the people working accounts actually see them.

A single customer view

Join Close's relationship data with billing, product, and support data in Databricks to build the customer picture the CRM alone cannot hold.

What you can sync between Close and Databricks

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.

Close objects Databricks objects
Opportunities Deal records with value, confidence, and status; commonly synced to reporting and billing systems. Volumes Unity Catalog file storage used for staging bulk loads.
Activities Calls, emails, SMS, notes, and meetings logged against a lead; the source for engagement analytics. SQL Warehouses The compute endpoint a sync connects to for query execution.
Tasks Follow-up items assigned to users; synced for workload and SLA reporting. Change Data Feed Row-level change records on Delta tables that drive incremental reads.
Custom Activities User-defined activity types with their own custom fields, mapped like standard activities. Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address.
Custom Fields Org-specific fields on leads, contacts, and opportunities; addressed by stable field ids in syncs. Schemas Group tables and views; syncs typically target a dedicated schema per source system.
Users Sales reps referenced as owners on leads, opportunities, and activities. Delta Tables The primary read and write target; operational data lands here as managed or external tables.
What ships with Close ⇄ Databricks

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Close or Databricks 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 Close or Databricks record.

Observability

Monitoring

Track your Close ⇄ Databricks sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Close and Databricks.

How the Close and Databricks connectors work

Close

Integration surface
REST API
Authentication
API key (sent via HTTP Basic auth)
Change detection
Webhook subscriptions for record events, with polling on date_updated fields for backfills
Capabilities
read · write · webhooks
Rate limits
Subject to per-endpoint rate limits communicated in response headers

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
How it works

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

    Choose tables

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

Close and Databricks 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 Close and Databricks.

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