Real-time
Real-time sync
Changes in Databricks or ZoomInfo instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ CRM
Databricks to ZoomInfo integration — real-time data sync
Keep Databricks and ZoomInfo 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
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Databricks and ZoomInfo
Flow ZoomInfo data into Databricks in real time — no exports, no schedulers, no custom scripts.
ZoomInfo is a read-only source: Stacksync reads its data in real time and delivers it into Databricks, so Databricks always reflects the current state of ZoomInfo — without exports, scripts, or schedulers.
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. Contact Profiles, Intent Signals, Scoops, Technographics from ZoomInfo land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in ZoomInfo. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Common use cases
- Sync intent signals into the CRM or warehouse to trigger outbound plays on in-market accounts.
- Fill gaps in new lead records (email, phone, company size) as they enter the CRM.
- 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.
Scores and segments back on the record
Lead scores, churn risk, or usage segments computed in Databricks appear as fields in ZoomInfo, where the people working accounts actually see them.
A single customer view
Join ZoomInfo's relationship data with billing, product, and support data in Databricks to build the customer picture the CRM alone cannot hold.
Cleanup that sticks
Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.
What you can sync between Databricks and ZoomInfo
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 | ZoomInfo objects | |
|---|---|---|
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Contact Profiles Person records with title, email, phone, and company linkage, used to enrich leads and contacts. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Intent Signals Company-level topic scores indicating in-market buying behavior. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Scoops Event-driven signals such as leadership changes, funding rounds, and new projects. | |
| Volumes Unity Catalog file storage used for staging bulk loads. | Technographics Technology install data per company, used for segmentation and territory planning. | |
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Company Hierarchies Parent and subsidiary linkage used to align CRM account hierarchies. | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Company Profiles Firmographic records covering industry, size, revenue, and location, matched against CRM accounts. |
What ships with Databricks ⇄ ZoomInfo
Connect Databricks and ZoomInfo for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–ZoomInfo connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or ZoomInfo 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 ZoomInfo record.
Observability
Monitoring
Track your Databricks ⇄ ZoomInfo 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 ZoomInfo.
How the Databricks and ZoomInfo 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
ZoomInfo
- Integration surface
- REST API organized around search and enrich endpoints
- Authentication
- API credentials exchanged for a short-lived JWT
- Change detection
- Scheduled re-enrichment and polling; the platform is primarily a lookup and enrichment source, not an event stream
- Capabilities
- read
- Rate limits
- Usage is metered by credits and contract-based limits rather than a single public rate limit.
How it works
How to connect Databricks to ZoomInfo — 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.
- 01
Connect your apps
Authenticate Databricks and ZoomInfo with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Databricks
connected
ZoomInfo
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and ZoomInfo 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.
objects · Databricks ⇄ ZoomInfoCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Databricks ZoomInfoCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and ZoomInfo integration FAQ
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Yes. Stacksync provides a managed, real-time integration between Databricks and ZoomInfo — ZoomInfo is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Databricks and ZoomInfo connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Databricks–ZoomInfo integration in-house.
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Yes — Stacksync ships production-grade connectors for both Databricks and ZoomInfo. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. On ZoomInfo: Scheduled re-enrichment and polling; the platform is primarily a lookup and enrichment source, not an event stream. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the ZoomInfo side: Contact Profiles, Intent Signals, Scoops, Technographics, plus custom fields where ZoomInfo exposes them. On the Databricks side: Views, Materialized Views, Volumes, SQL Warehouses. Stacksync auto-detects both schemas and converts types between the two systems.
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ZoomInfo is a read-only source, so this integration runs one-way: Stacksync reads from ZoomInfo in real time and delivers into Databricks. Field mapping and monitoring work the same as for two-way pairs.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and ZoomInfo.
Popular · 8 of 386
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Databricks ⇄ Creatio CRM -
Databricks ⇄ Drift -
Databricks ⇄ Folk CRM -
Databricks ⇄ Freshsales -
ZoomInfo ⇄ StarRocks -
ZoomInfo ⇄ Teradata Vantage -
ZoomInfo ⇄ Tinybird -
ZoomInfo ⇄ Vertica
No integrations match .
