Real-time
Two-way sync
Changes in Apollo.io or Databricks instantly reflect in both systems. No stale data, no manual imports.
CRM ⇄ Data warehouse
Apollo.io to Databricks integration — real-time, two-way sync
Keep Apollo.io 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
Case study
Migrated from Mulesoft
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Migrated from Celigo
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Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Apollo.io and Databricks
Sync Apollo.io 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. People (database records), Sequences, Deals (Opportunities), Tasks and calls from Apollo.io land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Apollo.io. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Common use cases
- Deduplicate contacts across Apollo and the CRM by syncing on email as the match key.
- Push CRM opportunity stages back into Apollo so reps see pipeline context while sequencing.
- Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
Scores and segments back on the record
Lead scores, churn risk, or usage segments computed in Databricks appear as fields in Apollo.io, where the people working accounts actually see them.
A single customer view
Join Apollo.io'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 Apollo.io 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.
| Apollo.io objects | Databricks objects | |
|---|---|---|
| People (database records) Prospects from Apollo's global database, pulled into downstream systems once enriched or saved. | Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | |
| Sequences Outreach cadences (emailer campaigns in the API); enrollment status is read to track which contacts are being worked. | Schemas Group tables and views; syncs typically target a dedicated schema per source system. | |
| Deals (Opportunities) Pipeline records that can be read and written to keep Apollo aligned with the CRM of record. | Delta Tables The primary read and write target; operational data lands here as managed or external tables. | |
| Tasks and calls Rep activity records synced for activity reporting and coaching workflows. | Views Curated read-only projections used as sync sources for downstream tools. | |
| Custom fields Account- and contact-level custom attributes mapped field-by-field in a sync. | Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | |
| Contacts People saved to your Apollo account, synced with emails, phone numbers, and enrichment fields. | Volumes Unity Catalog file storage used for staging bulk loads. |
What ships with Apollo.io ⇄ Databricks
Connect Apollo.io and Databricks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apollo.io–Databricks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apollo.io 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 Apollo.io or Databricks record.
Observability
Monitoring
Track your Apollo.io ⇄ Databricks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Apollo.io and Databricks.
How the Apollo.io and Databricks connectors work
Apollo.io
- Integration surface
- REST API
- Authentication
- API key (passed in request headers); master keys unlock account-wide endpoints
- Change detection
- Polling on updated-at timestamps; webhook callbacks exist only for delivering asynchronous enrichment results, not as a general change-event stream
- Capabilities
- read · write
- Rate limits
- Rate limits and enrichment credits vary by plan; bulk endpoints are throttled separately from single-record calls
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 Apollo.io 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.
- 01
Connect your apps
Authenticate Apollo.io 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.
Apollo.io
connected
Databricks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apollo.io 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.
objects · Apollo.io ⇄ DatabricksCustomers 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.
Apollo.io DatabricksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apollo.io and Databricks integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Apollo.io and Databricks: authenticate both systems, choose the objects to sync (such as Apollo.io's People (database records) and Sequences), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Apollo.io side: People (database records), Sequences, Deals (Opportunities), Tasks and calls, plus custom fields where Apollo.io exposes them. On the Databricks side: Delta Tables, Views, Materialized Views, Volumes. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Apollo.io and Databricks: Scores and segments back on the record; A single customer view; Cleanup that sticks. Lead scores, churn risk, or usage segments computed in Databricks appear as fields in Apollo.io, where the people working accounts actually see them.
-
Apollo.io: REST API. Authentication: API key (passed in request headers); master keys unlock account-wide endpoints. Databricks: 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. Stacksync manages authentication, retries, and rate limits on both sides.
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Apollo.io: Apollo distinguishes between people in its global database and contacts saved to your account; only saved contacts carry your custom fields and sequence history. Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Stacksync's field mapping accounts for these differences between Apollo.io and Databricks without custom code.
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 Apollo.io and Databricks.
Popular · 8 of 386
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Apollo.io ⇄ IBM Netezza -
Apollo.io ⇄ Materialize -
Apollo.io ⇄ Rockset -
Apollo.io ⇄ Starburst Enterprise -
Databricks ⇄ Nutshell -
Databricks ⇄ Oracle CX Sales -
Databricks ⇄ Outreach -
Databricks ⇄ Salesloft
No integrations match .
