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Data warehouse ⇄ CRM

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

Keep Databricks and Nimble 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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Migrated from Mulesoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Databricks and Nimble

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

Common use cases

  • Keep deals aligned between Nimble and an accounting system so invoicing starts when a deal closes.
  • Consolidate contacts from marketing tools into Nimble while writing Nimble edits back to avoid duplicates.
  • 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 Nimble 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 Nimble, where the people working accounts actually see them.

A single customer view

Join Nimble'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 Databricks and Nimble

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 Nimble objects
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Tags Segmentation labels that map to list membership or filters in downstream systems
Volumes Unity Catalog file storage used for staging bulk loads. Custom fields Account-defined contact attributes that carry enrichment or internal identifiers
SQL Warehouses The compute endpoint a sync connects to for query execution. Contacts Person records with multi-value fields for email, phone, and social profiles; the primary sync entity
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Companies Stored as contact records with a company record type, so they sync through the same contacts resource
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Deals Pipeline records linked to contacts, synced to keep revenue systems aligned with sales activity
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Tasks To-do items tied to contacts, mirrored into work-management tools or reporting tables
What ships with Databricks ⇄ Nimble

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Nimble 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 Nimble record.

Observability

Monitoring

Track your Databricks ⇄ Nimble 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 Nimble.

How the Databricks and Nimble 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

Nimble

Integration surface
REST API (JSON)
Authentication
API key; OAuth 2.0 available for registered applications
Change detection
polling on record modification timestamps
Capabilities
read · write
Rate limits
subject to per-account API request quotas
How it works

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

    Choose tables

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

Databricks and Nimble 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 Databricks and Nimble.

Popular · 8 of 386
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