Two-way sync
Changes in Databricks or Nutshell instantly reflect in both systems. No stale data, no manual imports.
Keep Databricks and Nutshell in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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. Tags, Users, Leads, People from Nutshell land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Nutshell. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Lead scores, churn risk, or usage segments computed in Databricks appear as fields in Nutshell, where the people working accounts actually see them.
Join Nutshell's relationship data with billing, product, and support data in Databricks to build the customer picture the CRM alone cannot hold.
Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.
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 | Nutshell objects | |
|---|---|---|
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Leads Nutshell's deal object; synced as the pipeline record linked to people and companies | |
| Volumes Unity Catalog file storage used for staging bulk loads. | People Individual contacts, kept consistent with marketing and outreach tools | |
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Companies Account records that group people and leads for account-level syncs | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Activities Logged calls, meetings, and emails used for engagement reporting | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Tasks Rep to-dos mirrored into external work-management or reporting systems | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Notes Free-text history attached to leads and contacts, replicated for a full timeline |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Nutshell connection.
Changes in Databricks or Nutshell instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Databricks or Nutshell data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Databricks or Nutshell record.
Track your Databricks ⇄ Nutshell sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Databricks and Nutshell.
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.
Authenticate Databricks and Nutshell with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Databricks and Nutshell 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Databricks and Nutshell: authenticate both systems, choose the objects to sync (such as Databricks's Materialized Views and Volumes), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. On Nutshell: Webhook subscriptions for record events, with polling as fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Nutshell side: Tags, Users, Leads, People, plus custom fields where Nutshell exposes them. On the Databricks side: Views, Materialized Views, Volumes, SQL Warehouses. Stacksync auto-detects both schemas and converts types between the two systems.
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.
Common patterns for Databricks and Nutshell: 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 Nutshell, where the people working accounts actually see them.
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. Nutshell: JSON-RPC API over HTTPS; a newer REST API is also offered. Authentication: HTTP Basic with account email and API key. Stacksync manages authentication, retries, and rate limits on both sides.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and Nutshell.