Real-time
Two-way sync
Changes in Cin7 or Databricks instantly reflect in both systems. No stale data, no manual imports.
ERP ⇄ Data warehouse
Cin7 to Databricks integration — real-time, two-way sync
Keep Cin7 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
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 Cin7 and Databricks
Put Cin7's records in Databricks as live tables for reporting and analysis, without extract jobs, and write results back where Cin7 can use them.
ERP data is some of the most asked-for data in the warehouse and some of the hardest to get: the record types are many, the APIs are strict, and extract jobs are brittle. Whether Cin7 carries financials, operations, workforce data, or all three, the analysis belongs in Databricks next to everything else the company measures.
Stacksync syncs Purchase orders, Contacts, Branches / locations, Stock adjustments and transfers from Cin7 into tables in Databricks continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in Databricks can be written back to fields in Cin7 where that is useful.
Common use cases
- 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.
- Publish Cin7 inventory levels to storefronts, marketplaces, and a CRM so every channel quotes real availability.
- Sync sales orders from Cin7 into an accounting platform or warehouse for revenue and margin reporting.
Where Cin7 runs operations: order and supply analysis
Operational records become queryable tables in Databricks, joinable with sales and finance data.
Group reporting across systems
Combine Cin7's records with data synced from other systems in Databricks for consolidated views no single system can produce.
Write-back where Cin7 exposes writable fields
Classifications or reference values computed in Databricks sync back onto the corresponding records in Cin7.
What you can sync between Cin7 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.
| Cin7 objects | Databricks objects | |
|---|---|---|
| Contacts Customers and suppliers, matched to CRM records to keep account data consistent. | SQL Warehouses The compute endpoint a sync connects to for query execution. | |
| Branches / locations Warehouse entities that scope every stock movement and order allocation. | Change Data Feed Row-level change records on Delta tables that drive incremental reads. | |
| Stock adjustments and transfers Inventory movements read for audit and reconciliation reporting. | Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | |
| Credit notes / returns Return documents synced so finance and support see the same refund state. | Schemas Group tables and views; syncs typically target a dedicated schema per source system. | |
| Products SKU records with options and pricing, synced with storefront and marketplace catalogs. | Delta Tables The primary read and write target; operational data lands here as managed or external tables. | |
| Inventory levels Stock on hand by branch or location, published outward for availability. | Views Curated read-only projections used as sync sources for downstream tools. |
What ships with Cin7 ⇄ Databricks
Connect Cin7 and Databricks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cin7–Databricks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Cin7 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 Cin7 or Databricks record.
Observability
Monitoring
Track your Cin7 ⇄ Databricks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Cin7 and Databricks.
How the Cin7 and Databricks connectors work
Cin7
- Integration surface
- REST API; note that Cin7 Omni and Cin7 Core (formerly DEAR Systems) are separate products with separate APIs
- Authentication
- API key credentials (paired with a username or account ID, depending on the product)
- Change detection
- Polling on modified-date filters; webhook support exists on some editions for order and stock events
- Capabilities
- read · write · webhooks
- Rate limits
- Subject to per-account API rate limits that differ between Cin7 Omni and Cin7 Core
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 Cin7 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 Cin7 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.
Cin7
connected
Databricks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Cin7 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 · Cin7 ⇄ 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.
Cin7 DatabricksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Cin7 and Databricks integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Cin7 and Databricks: authenticate both systems, choose the objects to sync (such as Cin7's Contacts and Branches / locations), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Databricks side: Views, Materialized Views, Volumes, SQL Warehouses, plus custom fields where Databricks exposes them. On the Cin7 side: Purchase orders, Contacts, Branches / locations, Stock adjustments and transfers. 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 Cin7 and Databricks: Where Cin7 runs operations: order and supply analysis; Group reporting across systems; Write-back where Cin7 exposes writable fields. Operational records become queryable tables in Databricks, joinable with sales and finance data.
-
Cin7: REST API; note that Cin7 Omni and Cin7 Core (formerly DEAR Systems) are separate products with separate APIs. Authentication: API key credentials (paired with a username or account ID, depending on the product). 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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Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Cin7: Inventory is modeled per branch/location, so availability syncs choose between per-location and aggregated quantities. Stacksync's field mapping accounts for these differences between Cin7 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 Cin7 and Databricks.
Popular · 8 of 386
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Cin7 ⇄ Greenplum -
Cin7 ⇄ IBM Netezza -
Cin7 ⇄ Materialize -
Cin7 ⇄ Rockset -
Databricks ⇄ Körber WMS -
Databricks ⇄ Linnworks -
Databricks ⇄ Logiwa WMS -
Databricks ⇄ Macola ERP
No integrations match .
