Was ist Databricks? Was ist die BDC? Die ultimative Anleitung für die perfekte Kombination!
- Big Data Analytics, Databricks, SAP BDC Databricks, SAP Business Data Cloud (BDC)
- 4 min reading time
Benjamin Bauert
In today's data-driven business world, the ability to efficiently analyze and utilize large amounts of data is crucial for business success. The combination of Databricks and the SAP Business Data Cloud (BDC) offers companies a powerful solution to take big data analytics, machine learning (ML), and real-time data processing to a new level. In this article, you will learn why the integration of these technologies is so promising, what possible use cases exist, and how your company can benefit from it.
Table of contents
1. What is Databricks?
Databricks is a cloud-based platform for data engineering and machine learning that is based on Apache Spark and Delta Lake (see Fig. 1). It was developed to efficiently process large datasets and simplify the training of AI models.
Why Databricks?
- High-Performance Data Processing:
With Apache Spark and SQL
- Zero-Copy-Sharing of SAP data:
Directly from SAP BDC via Delta Sharing
- Managed Data Platform:
Automatic management of computing power and memory
- Easy collaboration:
Support for Databricks Notebooks (Python, SQL) and local IDEs (VS Code, PyCharm).
- Continuous Integration & Delivery (CI/CD):
Git-supported development, integrated CI/CD workflows and repositories
- Unified Data Management with Unity Catalog:
Centralized governance, fine-grained access control, and traceability across all data assets
- Mosaic AI for domain-specific solutions:
Intelligent agent systems based on customized AI models that you can train and use on your proprietary data
(Source: Databricks, SAP)
2. What is the SAP Business Data Cloud (BDC)?
The SAP Business Data Cloud (BDC) is SAP's latest, forward-looking Data & Analytics product suite. It combines the strengths of established SAP solutions such as SAP BW, SAP Datasphere, and SAP Analytics Cloud (SAC) in a flexible, scalable platform. This integration is further enhanced by incorporating AI and machine learning functions from platforms like Databricks.
Why SAP BDC?
- Seamless Integration:
Enables the effortless integration of your existing data landscape into the cloud, ensuring continuity and accessibility.
- Increased Flexibility:
Offers more options for BW-on-HANA customers and enables adaptable data management solutions.
- Advanced Analytics:
Leverage real-time data processing and AI-driven insights to make informed, data-driven decisions.
- Scalability:
A cloud-based infrastructure that grows with your company's needs and guarantees optimal performance at all times.
By uniting these powerful tools, SAP BDC redefines how companies can efficiently use their data, promote innovation and remain competitive in today's data-driven landscape.
(Source: SAP)
Learn more about SAP BDC here.
3. Why is the combination of Databricks and BDC so powerful?
The integration of Databricks and SAP BDC combines the strengths of both platforms, creating an extremely effective solution for data-driven companies.
The perfect combination:
- Curated SAP Data Products:
The SAP Business Data Cloud primarily manages SAP application data and presents it in a structured, semantic "data product" format.
- Big Data Engineering & AI:
Databricks serves as an ideal environment for large-scale data processing, analytics, machine learning, and AI
- Seamless Integration:
Companies can store certain data sets exclusively in Databricks and still make them accessible for SAP analytics and AI use cases through zero-copy sharing (see Fig. 1).
- Easy provisioning:
Via “SAP for Me”, including user management
Source: SAP
4. Possible Use Cases
How can companies use this combination? Here are three key areas where SAP BDC and Databricks offer significant added value:
AI-supported decision-making with Mosaic AI
Use case: Domain-specific AI for business processes
Companies can develop AI models that are trained on their private SAP data to create industry-specific AI agents. For example, in supply chain management, AI can optimize demand forecasting, automate order processing, and provide real-time recommendations. Databricks enables scalable AI training, while SAP BDC ensures seamless integration into business processes.
Seamless integration of third-party data
Use case: Unified data landscape for better decision-making
Companies often need to combine SAP data with external sources such as CRM, market data, or IoT streams. By integrating these data sets into Databricks, organizations gain a 360° view of their operations. This enables business users to make better decisions, while SAP analytics tools can access enriched data in real time via zero-copy sharing.
Big Data with Apache Spark & SQL
Use case: High-performance data processing for large amounts of data
Companies that process large amounts of data such as transaction logs or IoT data streams require efficient and scalable solutions. Apache Spark, the core of Databricks, offers fast, distributed data processing and supports SQL for flexible queries. This combination simplifies ETL and ELT processes, supports advanced analyses and enables seamless integration with SAP data for real-time reporting and AI-supported insights.
5. Conclusion & Outlook
The integration of Databricks and the SAP Business Data Cloud represents a powerful solution for companies, enabling scalable, secure, and high-performance data processing, thus supporting data-driven decisions in real time.
Why should companies rely on Databricks + SAP BDC?
✅ Seamless integration of third-party data
✅ Fast analytics & Machine Learning with custom AI agents
✅ Easy data exchange with Delta Sharing
✅ Unified governance and access control with Unity Catalog
What's next?
As of February 2025, the SAP Business Data Cloud is in a controlled general availability phase for selected customers. The broader rollout is planned for later in the year and aims to provide companies with a scalable, secure, and powerful data processing solution.
By introducing SAP BDC in combination with Databricks, companies are positioning themselves at the forefront of data innovation. They are ready to use integrated analytics and AI to drive growth and remain competitive in the evolving digital landscape.
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