Earlier this month, SAP announced the launch of SAP Business Data Cloud (SAP BDC) at their SAP Business Unleashed 2025 event. Any time there's a big announcement like this, it raises a lot of questions—especially for companies that are already at a crossroads trying to determine their long-term data strategy in the AI age.

With that in mind, we thought we'd take to these airwaves to help you understand what SAP BDC is (and isn't), how we got here, and where things are headed. Along the way, we'll also explore how SAP BDC stacks up against leading solutions from other competitors, giving you a clearer picture of how it fits into the evolving data landscape.

SAP BDC: How Did We Get Here?

SAP has been in the enterprise data game for a long time—going all the way back to SAP Business Warehouse (SAP BW) in 1998. For years, SAP BW was the go-to solution for organizations looking to consolidate and analyze their SAP data in a structured, centralized way. But as business needs have evolved and data landscapes have become more complex, SAP has struggled to keep up—continuously expanding its portfolio to adapt to new technologies, rising data volumes, and the growing demand for real-time insights.

Now, with the introduction of SAP Business Data Cloud (SAP BDC), SAP is taking its biggest leap yet—bringing everything together into a single, all-in-one data platform designed for the AI era. This shift follows a broader industry move toward open, flexible, and AI-powered data architectures, breaking down silos and making enterprise data more accessible. But to really understand why SAP BDC exists and what problems it solves, it helps to take a quick look back at SAP’s journey from BW to Datasphere—and everything in between.

From BW to Datasphere

Although SAP has rolled out plenty of new data products in recent years, most have been geared toward self-service analytics and visualization rather than core data management. Tools like SAP BusinessObjects, SAP Lumira, SAP Business Explorer (BEx), and SAP Analytics Cloud (SAC) have made it easier for business users to access and analyze data, but SAP’s underlying data platforms—the backbone of enterprise data warehousing and governance—have evolved at a much slower pace.

For years, SAP BW was the foundation of SAP-centric data warehousing, offering structured modeling and deep integration with SAP ERP and Business Suite systems. While there were a few branding updates along the way (like the shift to SAP NetWeaver), the core product remained largely unchanged for over a decade, as shown in Figure 1 below.

Figure 1: Evolution of SAP Data Products Over Time

Things started to change with the introduction of SAP HANA in 2010 and the subsequent release of SAP BW/4HANA in 2016. By leveraging in-memory computing, a streamlined architecture, and improved integration tools, SAP was able to modernize the core BW platform, making it faster and more efficient.

But there was still one big problem—BW remained largely focused on SAP data. And as the world of data evolved, that limitation became harder to ignore.

Here’s why:

• The Explosion of Non-SAP Data – Corporate data estates were growing at an exponential rate, and things really took off with the rise of mobile devices, particularly after the iPhone launched in 2007. To put it in perspective, global data consumption jumped from approximately 2 zettabytes in 2010 to over 149 zettabytes in 2024. While SAP data was still critical, companies needed a unified platform where they could bring all their data together to make better decisions.

• Unstructured Data Overload – New data sources weren’t just growing in size—they were also becoming less structured. From social media and IoT sensor data to PDFs and video files, unstructured data exploded. The problem? Traditional data warehouses like BW and BW/4HANA thrive on structured data and predefined schemas, making them ill-equipped to handle the complexity of modern data landscapes.

• Scalability Challenges – As data volumes skyrocketed, BW customers found themselves struggling to scale. Handling massive spikes in data wasn’t easy, and integrating BW with Big Data technologies like Apache Spark was far from seamless.

Realizing that a more flexible and federated approach was needed, SAP began developing cloud-native data solutions on SAP Business Technology Platform (SAP BTP). This journey started with SAP Analytics Cloud (SAC) in 2015 and continued with SAP Data Intelligence in 2019.

But the real game-changer came in 2023 with the introduction of SAP Datasphere—a true data fabric solution designed to unify SAP and non-SAP data while preserving business context. Unlike its predecessors, Datasphere isn’t tied to ABAP and doesn’t require complex data replication. Instead, it enables seamless, federated access to data across hybrid and multi-cloud environments.

With Datasphere, SAP extended what Data Intelligence started—introducing advanced data cataloging, AI-driven governance, and native integrations with modern platforms like Databricks, Google BigQuery, and Snowflake. This marked a major shift in SAP’s data strategy, moving away from traditional, rigid data warehousing toward a more open, business-centric approach—one that helps organizations unlock the full value of their data in real time.

SAP's Unstructured Data Problem

As we noted in the previous section, unstructured data and data from non-SAP data sources has been a major problem for SAP for a long time. While SAP made several attempts to bridge the gap—first with SAP Vora and later with SAP Data Intelligence—the reality for most organizations was that their data remained scattered across multiple systems, making it difficult to manage and even harder for business users to access.

For many SAP customers, this meant juggling three separate data environments:

• SAP-centric data sat in an on-premises SAP BW or BW/4HANA system.

• Non-SAP data, along with some duplicated SAP data, lived in a cloud-based platform like Snowflake, Azure, or Google BigQuery.

• Semi-structured and unstructured data was stored in a corporate data lake, typically in the cloud.

As you can see in Figure 2 below, this fragmentation created serious challenges—not just for IT teams trying to manage these environments but also for data consumers who needed to navigate multiple systems just to get the full picture.

Figure 2: More Data Repositories = More Problems

It All Comes Together with Databricks

While Datasphere's open architecture was a move in the right direction, SAP still needed to expand its data platform to offer better support for non-SAP and unstructured data sources. To address this, SAP recently partnered with Databricks, a leader in data engineering, AI, and machine learning, to enhance Datasphere’s ability to handle diverse data landscapes.

Founded in 2013 by the creators of Apache Spark, Databricks has built a strong reputation with its lakehouse architecture, which combines the best of data lakes and data warehouses to manage structured, semi-structured, and unstructured data in a single, scalable environment.

By integrating with Databricks, SAP is giving customers a more practical way to blend SAP data with external datasets and take advantage of large-scale data processing and AI-driven analytics. While similar capabilities have been available through other platforms for some time, this partnership allows SAP customers to work with live, federated data across SAP Datasphere and Databricks without the need for extensive data replication. It’s another step towards aligning SAP’s data platform with modern, open data ecosystems, making it easier for businesses to manage and analyze all their data in one place.

Figure 3: Positioning of Databricks within SAP BDC

From PaaS to SaaS: An Evolution Towards All-in-One Data Platforms

While SAP BDC represents a huge leap forward for SAP, it's worth noting that SAP is actually playing a little bit of catch-up here. The push toward all-in-one data platforms has been happening for a while now. It started with managed cloud platform offerings like Snowflake and Databricks. Then, in 2023, Microsoft introduced Fabric as a full-blown SaaS offering. These modern data platforms bring data integration, storage, analytics, data science, and AI together under one roof, eliminating the need for businesses to cobble multiple services together just to get a complete data picture.

Figure 4 below shows how SAP BDC stacks up against some of the other industry leaders. While this list is by no means comprehensive, it's helpful to see how SAP BDC is positioned in the marketplace.

Figure 4: How SAP BDC Compares to Other Leading Platform Offerings

Overall, this industry-wide shift towards managed all-in-one style offerings is a huge win for customers:

1. Data Centralization: You now have the ability to manage your entire data estate under one roof, eliminating the silos that traditionally existed between data warehouses, data lakes, and AI platforms.

2. Data Landscape Complexity: Data landscapes become significantly less complex to set up and manage, requiring fewer separate integrations and reducing the time-to-value for data initiatives.

3. Cloud Scalability: With cloud scalability baked in, these modern data platforms can grow seamlessly with your business, ensuring that as your data needs expand, the infrastructure is already in place to support it. For example, instead of figuring out how to scale your Apache Spark cluster, the managed service does it for you automagically.

4. Skillset Consolidation: By consolidating tools and skillsets, businesses can reduce operational overhead and streamline workflows, making it easier for data teams to focus on insights rather than managing infrastructure.

5. Data Accessibility: This shift also makes it easier for data consumers of all types—business analysts, data scientists, and executives—to access and use data, whether for reporting, AI-driven insights, or real-time decision-making.

Ultimately, when done correctly, this shift transforms data from being a fragmented, IT-driven asset into a unified, business-driven powerhouse, enabling faster insights, smarter decisions, and greater innovation at scale.

Closing Thoughts

SAP BDC is a welcome addition to SAP’s data products portfolio, providing a unified, cloud-based solution for managing and analyzing enterprise data. With its deep integration into the SAP ecosystem, it’s a strong option for businesses that rely heavily on SAP solutions and want to keep everything under one roof.

But the real winner in all of this is you—the customer. The modern data landscape offers tremendous choice, allowing businesses to pick the platform that best aligns with their needs, whether it’s SAP BDC, Microsoft Fabric, Google BigQuery, or another solution.

If you're an SAP customer who prefers to go all-in with SAP, then BDC unlocks many powerful features, ensuring seamless integration with SAP S/4HANA, BW/4HANA, Datasphere, and AI services. Naturally, SAP BDC is designed to work best with SAP products, making it a strong choice for businesses that want a fully integrated SAP data stack.

On the other hand, if you're looking for broader flexibility, best-in-class AI/ML tools, or multi-cloud capabilities, platforms like Microsoft Fabric, Google BigQuery, or Snowflake may offer more advanced capabilities and a richer development ecosystem.

At the end of the day, there's no single right or wrong answer—each solution has its pros and cons, and the best choice depends on your business strategy, existing technology investments, and future scalability needs. As long as we can all agree to leave the ancient, monolithic data warehouses behind, we’re moving in the right direction. 😊