This is the first blog in our SAP + Databricks series. This part focuses on the business value and strategic importance of the partnership. A follow-up blog will dive deeper into technical architecture and implementation guidance.
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The enterprise world is entering a new phase of data maturity. After years of collecting, cleansing, and reporting on data, companies are now asking a different question: How do we make all this intelligence actually useful?
That shift has been driven by two realities. First, AI has moved from experimentation to expectation—business leaders now assume every workflow should be faster, predictive, and more connected. Second, the data that fuels those systems still lives inside complex, mission-critical platforms like SAP, which were never built for open, AI-ready access.
What makes 2025 different is that SAP is no longer acting like a closed monolith. Its partnership with Databricks signals a clear shift toward openness, where SAP accepts that innovation will increasingly happen outside the ERP, not inside it. And Databricks, already becoming the default AI engine for many enterprises, is now stepping into the role of unifying layer: the place where SAP data can be shared, modelled, governed, and activated without painful duplication.
This blog explores what this shift really means: the business context, the partnership, the architectural value, and the practical outcomes for teams who depend on SAP data every day.
Databricks Becoming the Enterprise AI Engine
Databricks has quietly become the backbone of modern data and AI innovation.
It’s where raw data turns into something meaningful – insights, models, predictions.
The platform brings together data engineering, analytics, and machine learning into one unified workspace, making it easier for teams to collaborate and scale. Whether it’s streaming data in real time or training large models, Databricks simplifies what used to take weeks into hours.
And then, there’s SAP, home to some of the most valuable enterprise data in the world.
From finance and supply chain to HR and operations, SAP holds the kind of structured, business-critical information companies run on. But it’s also known for its complexity. Data often sits in silos, locked away in systems that don’t easily talk to others.
That’s where things get interesting because bringing SAP and Databricks together means connecting the most powerful enterprise data with the most flexible AI platform.
It’s like giving SAP data a new life: faster insights, predictive intelligence, and a chance to turn every business process into a smarter one.
What Is SAP Databricks?
In early 2025, SAP and Databricks launched a joint platform that bakes Databricks’ analytics and AI chops directly into the SAP Business Data Cloud. Imagine having a single engine for real-time dashboards, AI predictions, and operational analytics, whether your data sits inside SAP or an external warehouse. No more drawn-out integrations, no more copy-paste headaches, just one place for all your analytics and machine learning.
SAP Databricks isn’t just another connector; it’s the missing piece that lets the business move at market speed, powered by insights that make sense, scale, and are safe to use. It’s SAP and AI, finally talking the same language, at the same table.
If choosing where to focus next, think about this: as more businesses embrace AI, the ones who get their data “house” in order first – open, unified, and compliant are the ones who get ahead. SAP Databricks is already making that possible for the world’s biggest brands.
SAP sells the offering as part of SAP Business Data Cloud and is available across major public clouds: Azure, AWS, and Google Cloud Platform.
SAP Databricks: Why This Partnership Changes Everything
1. Instant AI Without Data Copies
Traditional methods for extracting SAP data are complex, costly, and time-consuming. The lack of consistency in retaining SAP context only adds to the challenge, making it difficult to develop high-quality AI applications rapidly.
Instead of shuffling files between systems, SAP Databricks lets you query, analyze, and build models on both SAP and non-SAP data—zero copies required. It’s not just efficient; it slashes infrastructure costs and speeds up delivery by weeks or even months.
Businesses leveraging real-time analytics see decision-making speeds go up by 33%, which means faster pivots and outsmarting the competition.
How It Works: Delta Sharing Technology
SAP Databricks integrates natively with SAP Business Data Cloud through Delta Sharing, enabling secure, bidirectional data access without physically copying data between systems. This means:
- Data stays governed and secured in the SAP-managed cloud storage
- It can be read and processed in Databricks at high speed
- No complicated ETL processes required
- Real-time data access for immediate insights
2. Business-Ready Governance Built In
All data, whether it’s a sales order, IoT feed, or third-party market index, is governed under Databricks Unity Catalog. This translates to detailed audit trails, access controls, and regulatory peace of mind as standard, not an afterthought.
Unity Catalog Provides:
- Centralized governance across all data and AI assets
- Compliance with regulations like GDPR, HIPAA, and SOC 2
- Fine-grained access controls at table, column, and row levels
- Complete lineage tracking for all data transformations
- Consistent security policies across multi-cloud environments
3. Massive Investment in Customer Success
Databricks and SAP are putting real skin in the game. Following Databricks’ $15 billion fundraise, they’ve earmarked $250 million to help clients migrate and accelerate AI projects using the new platform.
4. What Teams Can Do Better Now
The impact of the SAP–Databricks partnership becomes real when you look at how everyday work changes. With faster access to connected, contextual data, teams can move from delayed reporting to timely decisions.
Supply Chain: Act Before Disruptions Spread
Planners can see order flows, supplier risks, and external signals together. They adjust plans earlier and prevent issues instead of reacting to them.
Finance: Model What’s Happening Right Now
Finance teams can analyze actuals and run scenarios as conditions shift. They understand margin impact sooner and make decisions with fewer delays.
Demand Planning: Forecast With Sharper Signals
Planners blend historical trends with live demand cues. Forecasts become more reliable, and adjustments happen in real time.
Operations: Prevent Problems, Don’t Chase Them
Maintenance teams spot early signs of equipment issues by combining operational patterns with performance data. They schedule interventions before breakdowns occur.
HR: Plan the Workforce With Clearer Insight
HR teams see skill gaps, attrition patterns, and talent trends sooner. Hiring and planning become more strategic and less reactive.
What Does This Mean for Real Teams?
For IT Leaders
Less time maintaining pipelines, more time pushing forward with genuine business-facing projects. The elimination of complex ETL processes and data duplication means IT teams can focus on innovation rather than infrastructure management.
For Business Functions
From finance to HR, the ability to mix and match SAP’s trusted data context with modern AI and predictive tools means decisions are smarter, and they arrive on time.
By bringing SAP data into the Databricks Data Intelligence Platform, organizations enable every business function from Finance to HR to anticipate, optimize, and execute with precision.
For Data Scientists and Analysts
No more spending half the week wrangling schemas. Everything is in one place, semantically linked and governed. Data scientists can focus on building models and deriving insights rather than battling data access issues.
How This Partnership Addresses Core Challenges
Many organizations aren’t held back by a lack of data; they’re held back by poor data quality and disconnected systems. When data lives in silos, it becomes difficult to harmonize and use effectively. As a result, innovation slows, decision-making becomes reactive, and teams struggle to move from insights to action.
Challenges with SAP Data:
Before SAP Databricks:
- Complex, one-directional data extraction processes
- Loss of business context and semantics during transfer
- Expensive and time-consuming integration projects
- Data duplication leading to inconsistencies
- Separate governance models create compliance risks
- High infrastructure costs
After SAP Databricks:
- Zero-copy data access with full context
- Bidirectional data sharing
- Unified governance and security
- Reduced infrastructure costs
- Faster time to insights
- Seamless collaboration across teams
Comparison with Other Popular Approaches
What's Next for SAP Databricks
The rapid growth of agentic AI requires organizations first to have the right data foundation. SAP Business Data Cloud ensures agentic AI is built on accurate, trusted data with business context.
Joule Integration SAP’s generative AI copilot, Joule, is deeply integrated with SAP Business Data Cloud. The knowledge graph connects data, metadata, and business processes, enabling AI agents and large language models to understand your business context.
Kenexai’s View of the SAP Databricks Opportunity
At Kenexai, we see the SAP–Databricks shift as a practical correction to years of complexity. SAP holds the most structured business data in the enterprise, but it was never designed for modern AI workflows. Databricks brings an open, flexible environment where that data can finally be used at speed and scale. Delta Sharing removes the old dependency on pipelines and extracts, letting teams work with SAP data in real time without breaking governance.
To us, the significance is straightforward: enterprises now have a clear, reliable way to turn SAP data into applied intelligence. The companies that move first will see faster decisions, cleaner architectures, and AI that supports real operations, not pilots.
FAQs: Your Questions Answered
SAP Databricks is a fully managed version of the Databricks Data Intelligence Platform, natively integrated into SAP Business Data Cloud. It combines SAP’s business-critical data with Databricks’ analytics, data engineering, and AI capabilities in a single, governed environment.
Organizations that:
- Run SAP systems (S/4HANA, Ariba, SuccessFactors, etc.)
- Want to leverage AI and advanced analytics on their SAP data
- Need to combine SAP data with external sources
- Require enterprise-grade governance and security
- Aim to accelerate their data and AI initiatives
Unlike traditional tools that focus primarily on reporting, SAP Databricks provides:
- Advanced machine learning and AI capabilities
- Real-time data processing
- Zero-copy integration with non-SAP data sources
- Open data lakehouse architecture
- Collaborative workspace for data teams
SAP Databricks is sold as part of SAP Business Data Cloud. Pricing is based on:
- Compute consumption (per DBU – Databricks Unit)
- Storage volumes
- Number of users
- Support level Contact SAP for specific pricing tailored to your needs.
While any SAP customer can benefit, we see particular traction in:
- Manufacturing: Predictive maintenance, quality control, supply chain optimization
- Retail: Demand forecasting, inventory management, customer analytics
- Financial Services: Risk modeling, fraud detection, regulatory reporting
- Healthcare: Resource optimization, patient outcome prediction, operational efficiency
- Consumer Goods: Market analysis, product innovation, supply chain resilience
The Future of Enterprise Data Is Here
The convergence of SAP’s unmatched business data with Databricks’ cutting-edge AI and analytics platform represents more than technological progress. It’s a fundamental shift in how enterprises create value from information.
The partnership between these two industry leaders has removed the traditional barriers, created the right incentives through massive investment, and proven the approach with real-world successes.
The only question that remains is: Will you lead, follow, or get left behind?
