The Active SAP Acquisition Landscape

The Active SAP Acquisition Landscape.

Did someone say we are in 2026? With the multiple recent acquisitions by SAP, it can feel like a throwback to the Bill McDermott years of 2018, when SAP seemingly made a major acquisition every few months. Since those heady days, the SAP ship has been steadied by the guiding hand of Christian Klein, with a view to accelerating the movement to the cloud. However, recent years have seen a new digital transformation mandate: the AI transformation. SAP has sometimes been accused of moving a little slowly in response to such market disruption, but, like the corporate juggernaut that they are, once they begin down the road, the momentum they gather can seem unstoppable. 

So, here is where we are today. The Artificial Intelligence move has disrupted the ERP space significantly, and the big tech corporations are scrambling to carve out their part of the pie. For SAP, the move to the Autonomous Enterprise encapsulates that, but in the acquisition space, their latest activity has aimed to plug white spaces in the approach. Last month, I discussed the SAP acquisition of Reltio, and what this meant for SAP customers. The dust had not even settled on this acquisition before SAP announced, in May 2026, two more significant purchases: Dremio and Prior Labs.

Let’s take a look into what makes these acquisitions significant in the broader context of the AI revolution.

Dremio is an open data lakehouse platform, whereas Prior Labs is a specialist AI research lab. Both of these acquisitions follow on neatly from the Reltio acquisition and are all designed to solve one of the most persistent problems in enterprise AI: the data isn't ready.

Both deals are pending regulatory approval. The Dremio acquisition is expected to close in Q3 2026, while the Prior Labs transaction is expected to close in Q2 or Q3 of 2026.

The problem SAP is trying to solve

SAP sits at the heart of global business operations, straddling finance, procurement, supply chain, HR, and more. However, in most enterprise-level organisations, SAP data doesn't live in isolation. It sits alongside data from Salesforce, Workday, legacy systems, data warehouses, and countless other sources. Getting all of that data into a usable, AI-ready state has historically required enormous effort, with complex ETL pipelines, format conversions, and brittle integrations that break under pressure. 

As the acquisition announcement from SAP stated, "Most enterprise AI projects fail to deliver value not because of the AI itself, but because the underlying data is fragmented, locked in proprietary formats and stripped of the business context that makes it meaningful."

These two acquisitions, in combination with upstream processes served by the like of SAP MDG or SimpleMDG, and with the downstream application of the newly acquired Reltio combining SAP and non-SAP data, are SAP's answer to that problem: provide a full end-to-end capability to ensure the AI models are supported by a robust, governed, and unified data infrastructure layer.

What is Dremio?

Dremio is an open data lakehouse platform. Founded in 2015 and based in Santa Clara, it had raised $410 million in venture capital funding before its acquisition. Its customers include Shell, TD Bank, and Michelin.

What makes Dremio strategically valuable to SAP is its architecture. With Dremio, SAP Business Data Cloud will become an Apache Iceberg-native enterprise lakehouse that unifies SAP and non-SAP data to power agentic AI at enterprise scale. 

A quick diversion into what Apache Iceberg is…

Apache Iceberg is rapidly becoming the industry-standard open table format. Iceberg sits on top of the data lake with standard functionality which makes it behave much more like a proper database rather than just a huge amount of data stored somewhere. The capabilities allow easy and concurrent reads and writes as well as amending how the data is organised on disc without having to rewrite the whole dataset. What is crucial is that Iceberg is vendor-neutral, meaning that data stored can be easily accessed by Snowflake, Databricks, Dremio, Spark, etc.

The key word here is “open”. In practical terms, the acquisition will let SAP and non-SAP data coexist on a single open foundation, extending federated analytics across enterprise data sources while combining with SAP HANA Cloud's in-memory engine for real-time transactions and operational performance. SAP will deliver a universal, open catalog built on Apache Polaris and the open Apache Iceberg REST Catalog API, serving as both the discovery and semantic layer of SAP's Business Data Cloud.

SAP CTO Philipp Herzig explains that, "Enterprise AI doesn't stall because the models aren't good enough; it stalls because the data isn't ready for AI agents. Dremio eliminates that bottleneck."

One notable complexity is that the move is complicated by similar offerings from existing SAP partners Snowflake and Databricks. However, analysts point to key differences with Dremio, particularly its ability to work with data while it sits in the enterprise's own environment, rather than requiring it to live externally. This is a meaningful distinction for large enterprises with strict data sovereignty or residency requirements.

What is Prior Labs?

While Dremio addresses the data infrastructure challenge, Prior Labs tackles the AI model itself.

Prior Labs is the pioneer of Tabular Foundation Models (TFMs), a new category of AI purpose-built for structured data. Founded by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, Prior Labs' TabPFN model series, published in Nature, set the state-of-the-art on tabular benchmarks across hundreds of independent academic studies.

This is significant because most of the AI buzz in recent years has centred on Large Language Models (LLMs), which is the technology behind ChatGPT and similar tools. But LLMs are primarily designed for language. Unlike LLMs, TFMs are purpose-built for the structured data that powers global business operations. These models provide accurate predictions regarding payment delays, supply chain vulnerabilities, and upsell opportunities by understanding tables and statistics natively.

For a company like SAP, whose entire value proposition is built on structured business data, this is a natural and powerful fit.

SAP has committed to investing more than €1 billion over the next four years to scale Prior Labs into a globally leading frontier AI lab. During this time, Prior Labs will continue to operate as an independent entity. The research team has been recruited from Google, Apple, Amazon, Microsoft, and leading quantitative finance firms, indicating that this is a serious research capability.

How do these acquisitions fit SAP's broader data and AI roadmap?

These deals don't exist in isolation. They are part of a deliberate and accelerating build-out of the SAP Business Data Cloud (SAP BDC).

Together, the acquisitions of Reltio (quality master data unification), Dremio (open lakehouse infrastructure), and Prior Labs (AI models for structured data) form three complementary layers of the same strategic vision.

SAP CEO Christian Klein noted on the company's Q1 earnings call that AI agents need to leverage multiple data types, and Dremio's Iceberg-based platform is designed to break down the data silos that currently prevent that. The overarching vision is an enterprise where AI agents don't just process SAP data, they reason across an organisation's entire data estate, from ERP to CRM to external sources, and take autonomous action within governed boundaries. 

What does this mean for SAP customers?

For organisations running SAP, whether on ECC, S/4HANA, or other cloud products, the implications are significant.

Easier integration of non-SAP data. One of the most persistent pain points for SAP customers has been getting non-SAP data into the same analytical environment without expensive, fragile pipelines. Dremio's lakehouse architecture directly addresses this, making it feasible to run analytics and AI across the full data estate without moving everything into a single proprietary store.

Better out-of-the-box AI predictions. Prior Labs' TFMs are purpose-built to predict the kinds of outcomes SAP customers care most about, such as payment delays, supply chain vulnerabilities, and upsell opportunities. Rather than building custom models from scratch, customers can expect these capabilities to become embedded in SAP products over time.

A more open platform. The commitment to Apache Iceberg and Apache Polaris signals that SAP is moving towards openness and interoperability rather than lock-in. This should give customers more flexibility in how they build their data and analytics stacks alongside SAP.

Faster time-to-value for AI initiatives. The combination of clean and governed data from SAP MDG or SimpleMDG, through to unified SAP and non-SAP data with Reltio, then on to a unified and open data lake with Dremio, then finally with AI models purpose-built for that data (Prior Labs) should meaningfully reduce the time and cost of getting enterprise AI from proof-of-concept to production.

Conclusion

These acquisitions are also part of a broader consolidation trend in the data and analytics market. This wave was triggered initially by Salesforce's acquisition of Informatica in late 2025. SAP has joined the party now, as enterprises seek to simplify complex AI pipelines and reduce the number of tools and vendors they manage.

For SAP, the message is clear: the company is no longer content to be the system of record that feeds other platforms. It wants to be the end-to-end data and AI platform for the enterprise. This means, in SAP’s vision, that SAP can be the place where business data lives, is governed, is understood, and is acted upon by intelligent agents.

Whether it can execute on that vision will depend on integration, adoption, and how quickly these capabilities land in the hands of customers. But the strategic direction is unambiguous, and for organisations deep in the SAP ecosystem, these are acquisitions worth watching closely.