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SAP to Acquire Dremio to Unify SAP and Non-SAP Data to Power Agentic AI

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SAP (NYSE: SAP) agreed to acquire Dremio to integrate SAP and non-SAP data and accelerate agentic AI. The deal, terms undisclosed, aims to make SAP Business Data Cloud an Apache Iceberg-native enterprise lakehouse with a universal open catalog, serverless performance, and a foundation for the SAP Knowledge Graph. The transaction is expected to close in Q3 2026, subject to customary closing conditions including regulatory approvals.

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Positive

  • Unifies SAP and non-SAP data on a single open lakehouse platform
  • Transforms SAP Business Data Cloud to be Apache Iceberg-native
  • Introduces a universal open catalog as SAP Knowledge Graph foundation
  • Serverless, elastic architecture to improve analytics economics
  • Combines lakehouse with SAP HANA Cloud for real-time transactions
  • Continued commitment to Apache Iceberg, Polaris, and Arrow open-source

Negative

  • Deal terms were not disclosed, limiting investor clarity
  • Transaction is pending regulatory approval, closing targeted for Q3 2026

News Market Reaction – SAP

+0.39%
+0.39% Session close to close

In the May 4 session, SAP gained 0.39%, reflecting a mild positive market reaction.

Data tracked by StockTitan Argus on the day of publication.

Market Context

This announcement highlights SAP’s continued focus on unifying SAP and non-SAP data to enable AI, ad...
Analysis

This announcement highlights SAP’s continued focus on unifying SAP and non-SAP data to enable AI, adding Dremio’s open lakehouse capabilities to SAP Business Data Cloud. Prior acquisition,AI deals such as Reltio and WalkMe showed modest, mixed price reactions. Investors may track execution milestones like regulatory approvals, closing timing in Q3 2026, and technical integration around Apache Iceberg and catalog capabilities, alongside broader metrics such as cloud backlog and revenue growth.

Key Figures

Cloud backlog: €21.9bn Cloud revenue: €5.96bn Total revenue: €9.56bn +5 more
8 metrics
Cloud backlog €21.9bn Q1 2026 current cloud backlog
Cloud revenue €5.96bn Q1 2026 cloud revenue
Total revenue €9.56bn Q1 2026 total revenue
Share buyback €10bn Announced repurchase program; first tranche partially completed
First tranche buyback €2.6bn Completed portion of €10bn buyback
Dividend €2.50 Proposed dividend alongside Q1 2026 results
Cloud guidance low end €25.8bn 2026 cloud revenue guidance at constant currencies
Cloud guidance high end €26.2bn 2026 cloud revenue guidance at constant currencies

Previous Acquisition,AI Reports

2 past events · Latest: Mar 27 (Positive)
Same Type Pattern 2 events
Date Event Sentiment 24h Move Catalyst
Mar 27 AI data acquisition Positive -1.8% Agreed to acquire Reltio to make SAP and non-SAP data AI-ready.
Jun 05 AI platform acquisition Positive +2.5% Entered deal to acquire WalkMe to enhance SAP Business AI offerings.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

Past AI-focused acquisitions prompted modest, mixed price reactions, with one positive and one negative move despite similar strategic themes.

Recent Company History

Recent history in the acquisition,AI category shows SAP repeatedly using M&A to make SAP and non-SAP data AI-ready. The Reltio deal aimed to unify master data for AI workflows, while the WalkMe purchase targeted digital adoption and Business AI enhancements. Reactions to these announcements were modest and directionally mixed, indicating that AI-focused acquisitions have not consistently driven strong upside, which frames today’s Dremio announcement as part of an ongoing data and AI consolidation strategy.

Key Terms

agentic ai, data lakehouse, apache iceberg, apache arrow, +3 more
7 terms
agentic ai technical
"platform built to accelerate agentic AI and expand SAP Business Data Cloud's ability"
Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.
data lakehouse technical
"Dremio, an open, high-performance data lakehouse platform built to accelerate"
A data lakehouse is a modern data platform that combines the large, inexpensive storage of a 'data lake' for raw information with the structured, query-ready features of a 'data warehouse,' so businesses can store everything and analyze it faster. For investors, it matters because it can lower data costs, speed up insight generation and reporting, and support better, timelier decisions about performance, risk and strategy—like having a single library that holds both raw manuscripts and an instant searchable catalog.
apache iceberg technical
"SAP Business Data Cloud will become an Apache Iceberg-native enterprise lakehouse"
Apache Iceberg is an open-source data table format that helps organizations store and manage very large analytical datasets reliably, like a version-controlled filing cabinet for huge amounts of information. It matters to investors because it makes financial reporting, auditing, and large-scale data analysis faster and more accurate while reducing storage and processing waste, which can improve operational efficiency, cost control and the transparency of a company’s reported results.
apache arrow technical
"open-source projects at the heart of its platform: Apache Iceberg, Apache Polaris and Apache Arrow"
Apache Arrow is an open-source way of organizing data in memory so different programs can read and process large tables much faster without copying or converting them. For investors, that speed and efficiency can mean cheaper, faster analytics and real-time signals from large datasets—like getting key figures from a spreadsheet instantly rather than waiting—helping firms make quicker trading, risk and research decisions.
semantic layer technical
"It serves as both the discovery and semantic layer of SAP Business Data Cloud"
A semantic layer is a translation layer that turns raw, technical data into consistent, business-friendly terms and metrics so non-technical users can ask questions and get reliable answers. For investors it matters because it makes financial reports and analytics comparable and easier to trust—like a common dictionary that ensures everyone is using the same definition of revenue, costs or customer counts, reducing confusion and speeding decision-making.
data lineage technical
"access rights and data lineage. This catalog will form the foundation"
Data lineage is a map that shows where a piece of data came from, how it moved and changed, and where it is used — like a package tracking history for information. For investors, clear lineage helps verify that financial metrics, risk models, or product analytics are built on reliable inputs, supports regulatory audits, and reduces the chance that decisions are based on corrupted or misunderstood data.
rest catalog api technical
"built on Apache Polaris and the open Apache Iceberg REST Catalog API. It serves"
A REST catalog API is a web-based interface that lets software query, retrieve and manage a searchable list of items—such as products, documents, securities, or data records—using simple internet requests. For investors, it acts like a live, machine-readable library catalog that provides fast, consistent access to up-to-date listings and metadata, enabling automated analysis, portfolio tools, trade workflows, and easier compliance checks.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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WALLDORF, Germany and AUSTIN, Texas, May 4, 2026 /PRNewswire/ -- SAP SE (NYSE: SAP) and Dremio today announced that SAP has agreed to acquire Dremio, an open, high-performance data lakehouse platform built to accelerate agentic AI and expand SAP Business Data Cloud's  ability to combine SAP and non-SAP data to more effectively run analytical and AI workloads in real time. Terms of the deal were not disclosed. The transaction is still pending regulatory approval.

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. The result is a familiar and costly pattern: pilots that cannot scale, slow integration of new data sources, duplicated engineering work and compliance risk when organizations cannot explain how an AI-driven decision was reached. Dremio helps eliminate that data fragmentation and integration friction. The acquisition will complement the SAP Business Data Cloud and SAP HANA Cloud offerings to ensure seamless data integration across SAP and non-SAP data with high performance and low cost to accelerate AI-ready context and time-to-value for AI.

"Enterprise AI doesn't stall because the models aren't good enough; it stalls because the data isn't ready for AI agents," said Philipp Herzig, CTO, SAP SE. " Dremio eliminates that bottleneck. Combined with SAP Business Data Cloud, we can now take customers from raw, fragmented data to governed, AI-ready intelligence on a single open platform."

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. Apache Iceberg is the industry-standard open table format, and SAP Business Data Cloud will natively support it as its foundation. This means no data movement or format conversion will be necessary. SAP and non-SAP data can coexist on the same open foundation, with federated analytical reach across every enterprise data source, combined with SAP HANA Cloud's in-memory engine for real-time transactions and operational performance.

The Dremio lakehouse platform is set to vastly improve the economics of enterprise analytics. It is serverless and elastic, scaling up automatically when demand spikes and scaling back down when it subsides, meaning no fixed capacity to provision and no performance ceiling when it matters most.

With Dremio, SAP will deliver a universal, open catalog built on Apache Polaris and the open Apache Iceberg REST Catalog API. It serves as both the discovery and semantic layer of SAP Business Data Cloud, giving every connected engine – SAP or non-SAP – a single point of access to unified business context: meaning, relationships, access rights and data lineage. This catalog will form the foundation of the SAP Knowledge Graph, embedding business relationships, organizational hierarchies, regulatory classifications and cross-system lineage as native properties.

Dremio has been a leading steward of open-source projects at the heart of its platform: Apache Iceberg, Apache Polaris and Apache Arrow,– and SAP is fully committed to continuing to invest in and prioritize these contributions.

The transaction is expected to close in Q3 of 2026, subject to customary closing conditions, including regulatory approvals.

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

About Dremio
Dremio is the Agentic Lakehouse: the only Iceberg-native data platform built for agents and managed by agents. Every knowledge worker and AI agent gets instant, governed access to enterprise data through any LLM or tool of their choice. Federated queries reach any source without ETL pipelines. An AI Semantic layer adds business context so every agent draws from the same source of truth. The lakehouse manages itself, running clustering, optimization, and compaction autonomously. The result: trusted insights that drive better business outcomes, without the infrastructure complexity or overhead.

A lead contributor to Apache Iceberg and co-creator of Apache Arrow and Apache Polaris. Trusted by Shell, TD Bank, Michelin, and thousands of organizations worldwide. https://www.dremio.com/

About SAP
As a global leader in enterprise applications and business AI, SAP (NYSE: SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP's 2025 Annual Report on Form 20-F.

© 2026 SAP SE. All rights reserved.
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SOURCE SAP SE

FAQ

What did SAP announce about acquiring Dremio on May 4, 2026 (SAP)?

SAP announced it agreed to acquire Dremio to unify SAP and non-SAP data and accelerate agentic AI. According to the company, the deal makes SAP Business Data Cloud Apache Iceberg-native and is expected to close in Q3 2026, subject to regulatory approvals.

How will the Dremio acquisition change SAP Business Data Cloud (SAP)?

The acquisition will make SAP Business Data Cloud an Apache Iceberg-native enterprise lakehouse with a universal open catalog. According to the company, this removes data movement and enables federated analytics across SAP and non-SAP sources while preserving business context.

When is the SAP and Dremio transaction expected to close (SAP)?

The transaction is expected to close in Q3 2026, subject to customary closing conditions. According to the company, closing remains conditional on regulatory approvals and other customary closing steps before completion.

Will Dremio remain committed to open-source projects after the SAP deal (SAP)?

SAP said it will continue to invest in and prioritize Dremio's open-source contributions. According to the company, stewardship of Apache Iceberg, Apache Polaris, and Apache Arrow remains a stated commitment post-acquisition.

What operational benefits does SAP expect from integrating Dremio (SAP)?

SAP expects serverless, elastic lakehouse performance that scales automatically for demand spikes and lowers fixed capacity needs. According to the company, this should improve analytics economics and speed time-to-value for AI-ready business context.