SAP acquires Dremio to unify data and accelerate enterprise AI agent deployment at scale

SAP dives deeper into Iceberg with Dremio acquisition

SAP has snapped up Dremio, a data integration and analytics provider, to extend the reach of its data analytics and AI agent-building tools into external data sources. The ERP giant spent an undisclosed sum on the Iceberg-based lakehouse biz in a bid to help its customers eliminate data fragmentation and improve integration. The purchase will, according to SAP, complement its data warehouse and analytics platform, Business Data Cloud, and SAP HANA Cloud. In a statement, SAP said the 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 an open table format that originated at Netflix. It has a rival in Databricks' Delta Lake format - open source under the Linux Foundation - although Databricks has moved to make the standards more interoperable since its acquisition of Tabular, a company founded by Iceberg's original authors. In both formats, the promise is to bring analytics to the data, without the cost and effort of moving it, helping to underpin enterprise analytics, machine learning, and AI agent development. SAP claims Apache Iceberg is the industry-standard open table format, and the Business Data Cloud will natively support it "as its foundation," meaning no data movement or format conversion is necessary. SAP has been here before. About three years ago, then-CTO Juergen Mueller pledged to help customers "easily and confidently integrate SAP data with non-SAP data from third-party applications and platforms," supported by its partnership with Databricks, the data lake and machine learning vendor. Last year, it deepened ties with Databricks to support bidirectional data sharing between SAP Business Data Cloud and third-party data platforms, with Databricks' Delta Lake open table format "as the initial delivery." The setup used Databricks' Delta Sharing, which was initially based on the Delta format, although the company has more recently announced support for Iceberg. Dremio was valued at $2 billion during a $160 million funding round in 2022. Whatever SAP paid for the vendor, it obviously felt it was worth the money to get more tech based on the Iceberg open table format, which is repeatedly emphasized in the announcement. It might leave some wondering what it was not getting from the Databricks partnership. The Register has asked SAP for further comment. SAP said the Dremio lakehouse platform would "vastly improve the economics of enterprise analytics," offering a serverless and elastic approach without fixed capacity to provision or performance ceiling. With the acquisition, SAP will give customers an open catalog built on Apache Polaris and the open Apache Iceberg REST Catalog API, to create a discovery and semantic layer for SAP Business Data Cloud. It promises "a single point of access to unified business context: meaning, relationships, access rights, and data lineage" across enterprise data outside SAP. ®

SAP to acquire data lakehouse vendor Dremio

Two existing SAP partners, Snowflake and Databricks, offer similar services, but there are key differences in Dremio's offerings that may speak to enterprise IT AI fears. SAP on Monday announced plans to acquire Dremio, which bills itself as an agentic lakehouse company, for an unspecified price. The move is complicated by similar offerings from existing SAP partners Snowflake and Databricks, but analysts point to key differences with Dremio, especially in its ability to work with data while it sits in the enterprise's environment, rather than having to live externally. One of SAP's justifications for the acquisition is that it will theoretically make it easier for IT executives to combine SAP data with non-SAP data. But its strongest rationale involves Dremio's ability to make complex data more AI-friendly, so that it can more quickly and cost-effectively be made usable. "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 SAP announcement said. "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."

SAP To Buy Dremio And Prior Labs To 'Lead' Agentic And AI Models

SAP unveils plans to acquire Dremio and Prior Labs to take its agentic AI portfolio and Tabular Foundation Models to the next level. SAP is elevating its AI strategy with the acquisitions of data lakehouse platform provider Dremio and AI foundational model specialist Prior Labs, along with a $1.1 billion investment commitment to scale Prior Labs. With the planned purchase of 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. "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 of SAP SE, in a statement. "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." [Related: AWS Vs. Google Cloud Vs. Microsoft Azure Q1 Earnings Face-Off] Tabular Foundation Model (TFM) pioneer Prior Labs looks to boost SAP's success in AI foundation models along with SAP's commitment to invest more than $1.1 billion to scale Prior Labs globally. "We built SAP-RPT-1 to prove that conviction for enterprise data," Herzig said. "Prior Labs has built a leading TFM on public benchmarks and built one of the leading research teams in this category. Combining their frontier model work with enterprise data and customer reach is how we intend to lead this category globally." Financial terms of both deals were not disclosed. Both deals are expected to close by the third quarter of 2026. Dremio provides an open data lakehouse platform built to accelerate agentic AI and expand SAP Business Data Cloud's capabilities. Dremio's Agentic Lakehouse is dubbed as the only Iceberg-native data platform built for agents and managed by agents. By acquiring Dremio, SAP will boost its 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. The Dremio lakehouse platform 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. SAP Business Data Cloud will natively support Apache Iceberg as its foundation. In addition, Dremio and SAP will provide a universal, open catalog built on Apache Polaris and the open Apache Iceberg REST Catalog API. SAP said Prior Labs will remain an independent company, with SAP pledging more than $1.1 billion over the next four years to scale the startup into a global frontier AI lab focused on enterprise structured data. SAP aims to establish an industry-leading AI research lab and shape a new category in TFMs. With over 3 million downloads, Prior Labs' TabPFN is a widely adopted open-source tool for tabular AI. SAP said large language models (LLMs) struggle to make accurate predictions on structured business data because they have only a rudimentary understanding of tables, numbers and statistics. Unlike LLMs, Tabular Foundation Models (TFMs) are purpose-built for structured data, enabling more accurate predictions of business outcomes such as payment delays, supplier risk, upsell opportunities and customer churn. After the deal finalizes, SAP and Prior Labs plan to turn its top AI research into enterprise-ready innovation, allowing customers to get even more value out of their tabular business data.