Real-time
Two-way sync
Changes in Databricks or SAP instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ ERP
Databricks to SAP integration — real-time, two-way sync
Keep Databricks and SAP 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 Fivetran
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Migrated from Celigo
Why teams connect Databricks and SAP
Put SAP's records in Databricks as live tables for reporting and analysis, without extract jobs, and write results back where SAP 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 SAP carries financials, operations, workforce data, or all three, the analysis belongs in Databricks next to everything else the company measures.
Stacksync syncs Production Orders, Inventory / Stock, Cost Centers, Business Partners from SAP 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 SAP where that is useful.
Common use cases
- Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
- Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
- Keep MES and WMS systems aligned with production orders and goods movements.
- Expose sales order and delivery status to customer portals through a synced Postgres database instead of direct SAP access.
Group reporting across systems
Combine SAP's records with data synced from other systems in Databricks for consolidated views no single system can produce.
Write-back where SAP exposes writable fields
Classifications or reference values computed in Databricks sync back onto the corresponding records in SAP.
Where SAP holds the books: finance reporting from live data
Financial records land in Databricks as they change, so period-end reporting queries current numbers rather than last night's extract.
What you can sync between Databricks and SAP
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 | SAP objects | |
|---|---|---|
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Production Orders Manufacturing orders exchanged with MES and scheduling systems. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Inventory / Stock Plant and storage-location quantities synced to storefronts and planning tools. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Cost Centers Controlling masters read for mapping costs in finance integrations. | |
| Volumes Unity Catalog file storage used for staging bulk loads. | Business Partners The unified customer and supplier master in S/4HANA, the anchor object for CRM and procurement syncs. | |
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Materials (Products) Item master with plant and sales views, synced to commerce, PLM, and CRM systems. | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Sales Orders Order documents written from external channels and read for status and fulfillment. |
What ships with Databricks ⇄ SAP
Connect Databricks and SAP for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–SAP connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or SAP 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 SAP record.
Observability
Monitoring
Track your Databricks ⇄ SAP 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 SAP.
How the Databricks and SAP 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
SAP
- Integration surface
- OData (v2/v4) APIs on S/4HANA; BAPI/RFC and IDoc on ECC and on-prem systems; SOAP services
- Authentication
- OAuth 2.0 or basic auth via communication arrangements on cloud editions; SAP user credentials for RFC on-prem
- Change detection
- Business events via SAP Event Mesh on S/4HANA; change pointers with IDocs or timestamp polling on ECC
- Capabilities
- read · write · webhooks
- Rate limits
- Throttling is configured at the gateway and tenant level rather than as a single published rate limit
How it works
How to connect Databricks to SAP — 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 SAP 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
SAP
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and SAP 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 ⇄ SAPCustomers 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 SAPCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and SAP integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Databricks and SAP: authenticate both systems, choose the objects to sync (such as Databricks's Delta Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. SAP: Direct access to the underlying HANA database is generally restricted, so change capture relies on business events, change pointers, or API polling rather than database-level CDC. Stacksync's field mapping accounts for these differences between Databricks and SAP 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 Databricks and SAP 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 Databricks and SAP connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Databricks–SAP integration in-house.
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Yes — Stacksync ships production-grade connectors for both Databricks and SAP. 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 SAP: Business events via SAP Event Mesh on S/4HANA; change pointers with IDocs or timestamp polling on ECC. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 SAP.
Popular · 8 of 386
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Databricks ⇄ Blue Yonder WMS -
Databricks ⇄ Brightpearl -
Databricks ⇄ Cetec ERP -
Databricks ⇄ Cin7 -
SAP ⇄ Yellowbrick -
SAP ⇄ Snowflake -
SAP ⇄ BigQuery -
SAP ⇄ MotherDuck
No integrations match .
