SAP Datasphere vs. SAP Databricks: smart combination or competitors?

“Stop the silo thinking. Make SAP and Microsoft work together.” That was the message in our earlier blog, focused on connecting SAP systems with Microsoft tools like Power BI and Microsoft Fabric. That same mindset now applies within SAP itself. With the launch of SAP Business Data Cloud, both Datasphere and Databricks are part of one platform. But how do they relate? Are they overlapping tools, or part of a bigger picture?

This blog helps you understand what this means in practice. Do you need to choose, or can both tools play a role in your analytics architecture?

What is SAP Business Data Cloud?

SAP Business Data Cloud is a shared data platform. It brings together trusted SAP data and new tools for data science and analytics. The platform consists of:

• A central object store where data is saved in open format (Delta Lake)

• A shared data catalog with metadata and access control

• SAP Datasphere for modeling and business logic

• SAP Databricks for working with data at scale using Python, SQL, Spark & R

The key idea: both tools access the same data, use the same security, and share the same business context.

What is the difference between SAP Datasphere and SAP Databricks?

SAP Datasphere and SAP Databricks are built for different user profiles and use cases within SAP Business Data Cloud. SAP Datasphere focuses on business modeling, semantics, and data governance. It is typically used by SAP BI consultants and data stewards who work with structured query language (SQL) and visual modeling tools like SAP Analytics Cloud. Its strength lies in embedding business meaning into data: applying security rules, defining dimensions, currencies, hierarchies, and making the data ready for enterprise reporting. In other words, it transforms raw data into trusted, interpretable assets for reporting and planning.

SAP Databricks, on the other hand, is designed for more advanced users, including data analysts, data engineers, and machine learning engineers. It offers a code-first environment using Python, Spark notebooks, and SQL to perform large-scale transformations, data science, and machine learning. Its key strengths are flexibility, scalability, and processing power. It allows users to easily integrate SAP and non-SAP data sources, make use of serverless compute for efficient resource management, and write processed data back to an object store for further use or consumption. This makes it ideal for running predictive models and building AI applications on top of integrated enterprise data.

SAP Datasphere and SAP Databricks serve different but connected roles within SAP Business Data Cloud. Datasphere provides structure, business context, and governance by applying business logic, defining dimensions, currencies, and hierarchies, and enforcing business-level access rules. Databricks builds on this foundation with large-scale processing, integration of external data, model training, and flexible access control through Unity Catalog.

Are they competitors?

Some people think so. The tools offer overlapping features like data transformation and catalog functions. Teams may also have different preferences: one group works with SAP tools, the other with Python and Spark.

But in the SAP Business Data Cloud, the tools are connected. The data lives in one place. You can model it in SAP Datasphere, and use it in SAP Databricks without copying it. You can also share insights back from Databricks into the same platform.

So while the tools serve different purposes, they do not compete. They can be part of one joint workflow.

How do they work together?

Shared data layer

Data products built in SAP Datasphere are stored as Delta files in the SAP object store. SAP Databricks can read these files directly. This avoids complex extract, transform and load steps. The access is fast and secure.

Shared governance

SAP Datasphere defines the semantics of the data. For example, currencies, units and business hierarchies. It also controls who is allowed to see what. This logic is reused in Databricks.

Different roles, same data

A finance data product can be created in SAP Datasphere, then used in different ways:

• For dashboards in SAP Analytics Cloud

• For forecasting models in SAP Databricks

What this means for your architecture

SAP Datasphere is your go-to environment when you need structured, governed, and trusted data for reporting, dashboards, and enterprise-wide analytics. It ensures that your data is semantically correct, compliant, and enriched with business logic, ready to be consumed by business users in a consistent way.

SAP Databricks, on the other hand, comes into play when you want to take that data further: integrating it with non-SAP sources, building advanced analytics pipelines, training machine learning models, or running scalable transformations. You do not have to choose one over the other. In fact, the best results come when your teams understand both domains combining business modeling and semantics with flexible, technical data engineering.

Our view

SAP made both tools part of one platform for a reason. Each has its own role, but together they make a stronger solution. Use SAP Datasphere to build meaning and control. Use SAP Databricks to scale & experiment.

You do not need to start big. Begin with one use case. Try a data product in Datasphere and explore it in Databricks. Learn what works. Then expand.

How to get started with SAP Databricks

SAP Databricks is currently in controlled availability. General rollout is expected in 2025. If you want to explore its capabilities, your SAP Datasphere tenant must be converted into a SAP Business Data Cloud tenant. This reconfiguration will be managed by SAP as part of their standard migration path.

To get started, begin small. Start with one use case. Create a data product in SAP Datasphere and explore it within SAP Databricks. Use that experience to learn what works best in your environment. Then scale from there as your needs grow and your team becomes more comfortable with both tools.

What you can do now?

Do you want to know if SAP Databricks fits your landscape? Or how you can get more value from SAP Datasphere? Contact us for a no-nonsense data assessment. We are happy to help you explore before you invest.