Real-time
Two-way sync
Changes in Clari or Databricks instantly reflect in both systems. No stale data, no manual imports.
CRM ⇄ Data warehouse
Clari to Databricks integration — real-time, two-way sync
Keep Clari 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
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Clari and Databricks
Sync Clari 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. Activity (Capture), Account field extensions, Opportunity field extensions, Audit Events from Clari land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Clari. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Common use cases
- 01 Enrich Clari Account records with firmographic or billing data points through the ingest API in incremental mode.
- 02 Stream Audit Events into a reporting database to monitor forecast-submission changes and user activity for compliance.
- 03 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- 04 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
Common sync patterns
Cleanup that sticks
Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.
CRM analytics on live data
Accounts, contacts, and activity from Clari 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 Clari, where the people working accounts actually see them.
What you can sync between Clari 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.
| Clari objects | Databricks objects | How this pairing syncs | |
|---|---|---|---|
| Audit Events User edits and system events exported with filtering by actor, session, and date range; read-only feed for change tracking and compliance. | Views Curated read-only projections used as sync sources for downstream tools. | Audit Events is specific to Clari and Views to Databricks — each maps to any object or custom field on the other side. | |
| Forecast Exported per forecast tab and fiscal period via async jobs; includes submitted forecast calls, updates, manager adjustments, and CRM totals. Read-only. | Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Forecast is specific to Clari and Materialized Views to Databricks — each maps to any object or custom field on the other side. | |
| Quota Quota and quota-history values exported alongside forecast data, scoped by fiscal quarter; read-only, useful for warehouse attainment reporting. | Volumes Unity Catalog file storage used for staging bulk loads. | Quota is specific to Clari and Volumes to Databricks — each maps to any object or custom field on the other side. | |
| Opportunities Retrieved synchronously by ID from GET /opportunity (up to 100 IDs per call) with Clari CRM scoring and field-change history; read-only, mirroring the CRM opportunity Clari sits on. | SQL Warehouses The compute endpoint a sync connects to for query execution. | Opportunities is specific to Clari and SQL Warehouses to Databricks — each maps to any object or custom field on the other side. | |
| Activity (Capture) Meetings, emails, and attachments captured by Clari and mapped to accounts and opportunities; exported read-only via async activity jobs. | Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Activity (Capture) is specific to Clari and Change Data Feed to Databricks — each maps to any object or custom field on the other side. | |
| Account field extensions External data points written onto Account records through the ingest API in initial or incremental mode; requires an apikey plus a partnerkey. | Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Account field extensions is specific to Clari and Catalogs to Databricks — each maps to any object or custom field on the other side. |
How changes propagate between Clari and Databricks
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
Clari Databricks Interval-based propagation
DetectionStacksync polls Clari for changes on an incremental schedule, reading only records changed since the previous pass. Polling — reads run as asynchronous export jobs (submit export, poll job status, download results).
DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.
Databricks Clari Sub-second propagation
DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.
DeliveryEach detected change is written to Clari through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Clari: Max 3 concurrent exports and roughly 1000 exports per rolling 30-day org window; ingestion capped at 100 requests/sec per API token.
- Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Clari ⇄ Databricks
Connect Clari and Databricks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Clari–Databricks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Clari 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 Clari or Databricks record.
Observability
Monitoring
Track your Clari ⇄ Databricks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Clari and Databricks.
How the Clari and Databricks connectors work
Clari
- Integration surface
- REST APIs on api.clari.com - Export API (v4, asynchronous bulk jobs for forecast, quota, activity, and audit) and Ingest API (v2, field extensions); Opportunity reads are synchronous via GET /opportunity
- Authentication
- API token in the apikey header, generated per user in Settings; ingest/partner endpoints also require a partnerkey header, and Copilot endpoints require X-Api-Key and X-Api-Password
- Change detection
- Polling — reads run as asynchronous export jobs (submit export, poll job status, download results); the ingest API supports an incremental mode for regular field updates. No webhooks.
- Capabilities
- read · write
- Rate limits
- Max 3 concurrent exports and roughly 1000 exports per rolling 30-day org window; ingestion capped at 100 requests/sec per API token.
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 Clari 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 Clari 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.
Clari
connected
Databricks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Clari 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 · Clari ⇄ 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.
Clari DatabricksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Clari and Databricks integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Clari and Databricks: authenticate both systems, choose the objects to sync (such as Clari's Audit Events and Forecast), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Common patterns for Clari and Databricks: Cleanup that sticks; CRM analytics on live data; Scores and segments back on the record. Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.
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Clari: REST APIs on api.clari.com - Export API (v4, asynchronous bulk jobs for forecast, quota, activity, and audit) and Ingest API (v2, field extensions); Opportunity reads are synchronous via GET /opportunity. Authentication: API token in the apikey header, generated per user in Settings; ingest/partner endpoints also require a partnerkey header, and Copilot endpoints require X-Api-Key and X-Api-Password. 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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Clari: No webhooks or change-data-capture; freshness depends on export cadence, bounded by roughly 1000 exports per rolling 30 days and 3 concurrent jobs per org. Databricks: Unity Catalog imposes a three-level namespace (catalog.schema.table) that governs access across workspaces. Stacksync's field mapping accounts for these differences between Clari and Databricks without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Clari and Databricks records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Clari and Databricks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Clari–Databricks integration in-house.
SECURITY
Security teams trust 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
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