SAP Bets Big on AI With Dremio, Prior Labs Buys

SAP is making its most aggressive move yet into the AI-powered data platform space, announcing plans to acquire Dremio, a leading open data lakehouse provider, and Prior Labs, a German AI startup specializing in tabular data intelligence. The twin acquisitions signal that the enterprise software giant is no longer content to simply bolt AI features onto its existing ERP products — it wants to own the full data-to-AI pipeline.

The deals represent a strategic pivot for SAP, positioning the Walldorf-based company to compete directly with the likes of Snowflake, Databricks, and Google BigQuery in the increasingly crowded enterprise data platform market. For SAP's massive installed base of over 400,000 customers worldwide, the implications are significant.

Key Takeaways From SAP's Acquisition Spree

• Dremio brings open data lakehouse technology built on Apache Iceberg, the fastest-growing open table format in the industry
• Prior Labs adds cutting-edge AI capabilities for tabular data analysis, a critical need for enterprise customers
• SAP is positioning its Business Data Cloud as a unified AI-ready platform that spans structured and unstructured data
• The acquisitions target SAP's biggest competitive weakness: making enterprise data accessible and AI-ready at scale
• Combined, these deals put SAP in direct competition with Databricks and Snowflake in the lakehouse market
• The moves align with SAP's broader Business AI strategy announced throughout 2024 and 2025

Dremio Gives SAP a Data Lakehouse Powerhouse

Dremio has built a reputation as one of the most innovative players in the open data lakehouse space. Founded in 2015, the company offers a SQL query engine that enables organizations to run analytics directly on data lakes without needing to copy or move data into proprietary warehouses.

The acquisition is particularly strategic because Dremio is built on Apache Iceberg, an open table format that has rapidly become the industry standard. Iceberg has gained massive traction among enterprises looking to avoid vendor lock-in, with adoption from companies like Netflix, Apple, and Adobe.

For SAP, Dremio solves a fundamental problem. Enterprise customers generate enormous volumes of data across SAP's ERP, supply chain, and finance systems, but accessing that data for AI and analytics has historically been cumbersome. Dremio's technology allows customers to query data in place, across multiple cloud environments, without expensive and time-consuming ETL processes.

This positions SAP's Business Data Cloud to become a true open data platform rather than a walled garden. Unlike competitors such as Snowflake, which still relies on data being loaded into its proprietary format, SAP can now offer a genuinely open approach that meets enterprise customers where their data already lives.

Prior Labs Brings AI-Native Tabular Intelligence

The Prior Labs acquisition is equally strategic, though less flashy. Prior Labs is a Berlin-based AI startup that has developed breakthrough models for understanding and analyzing tabular data — the spreadsheets, databases, and structured records that form the backbone of enterprise operations.

While large language models like GPT-4 and Claude excel at processing text and images, they struggle with the structured numerical and categorical data that enterprises depend on. Prior Labs has built AI models specifically designed to extract insights from tables, predict outcomes, and identify patterns in structured datasets.

This capability is critical for SAP's ambitions. The company's customers rely on massive volumes of tabular data across finance, supply chain, HR, and procurement workflows. By integrating Prior Labs' technology, SAP can offer AI capabilities that are specifically tuned for the types of data its customers actually use — not just general-purpose language models repurposed for enterprise tasks.

The acquisition also reflects a growing recognition across the industry that domain-specific AI often outperforms general-purpose models for enterprise use cases. Companies like Salesforce with its Einstein platform and Oracle with its embedded AI features have made similar bets on specialized AI capabilities.

SAP Enters a Three-Way Battle for Enterprise Data Dominance

The competitive landscape for enterprise data platforms has never been more intense. SAP's acquisitions put it on a direct collision course with 2 formidable rivals:

• Databricks, valued at $62 billion, has built its empire on the lakehouse concept and recently acquired Tabular, the company behind Apache Iceberg, for over $1 billion
• Snowflake, with a market cap exceeding $50 billion, has been aggressively adding AI features through its Cortex platform and recently embraced Iceberg as an open format
• Microsoft Fabric has emerged as another major contender, leveraging its Azure cloud infrastructure and tight integration with enterprise tools
• Google BigQuery continues to expand its AI and analytics capabilities within the Google Cloud ecosystem

SAP's unique advantage in this battle is its unrivaled access to enterprise business data. No other company has the same depth of integration into core business processes — from financials to supply chain to human resources. If SAP can make this data easily accessible and AI-ready through its enhanced platform, it could leapfrog competitors who have superior technology but less access to high-value business data.

However, SAP also faces a significant challenge: its track record with acquisitions has been mixed. The company's $8 billion purchase of Qualtrics in 2019, followed by its spin-off and eventual sale to Silver Lake in 2023, raised questions about SAP's ability to integrate acquired companies effectively.

Why Enterprise Data Is the Real AI Bottleneck

The timing of SAP's acquisitions reflects a broader industry truth: data readiness, not model capability, is the primary bottleneck for enterprise AI adoption. Most large organizations have invested heavily in AI tools and platforms, but they struggle to make their data accessible, clean, and structured enough to feed AI models effectively.

Recent surveys suggest that up to 80% of the time spent on AI projects goes into data preparation and engineering rather than model development. This 'data gap' is where SAP sees its biggest opportunity.

By combining Dremio's data lakehouse technology with Prior Labs' tabular AI models and its own vast enterprise data footprint, SAP aims to create a platform where:

• Business data from ERP, CRM, and supply chain systems is automatically accessible for AI workloads
• Open formats like Apache Iceberg eliminate vendor lock-in and enable multi-cloud flexibility
• Purpose-built AI models understand enterprise data structures natively
• Real-time analytics and AI predictions run directly on live business data without complex pipelines
• Governance and compliance controls are built into the data layer from the start

This vision, if executed well, could make SAP the default AI platform for enterprises that already run their core operations on SAP software.

What This Means for Enterprise Customers and Developers

For SAP's existing customer base, these acquisitions could be transformative. Organizations that have struggled to extract AI value from their SAP data may finally get a streamlined path from data to insights. The Dremio integration should make it easier to query and analyze data across hybrid and multi-cloud environments without extensive data engineering.

Developers building on SAP's platform can expect new APIs and tools for accessing lakehouse data and integrating tabular AI models into business applications. The open standards approach — particularly the embrace of Apache Iceberg — should also make it easier to combine SAP data with non-SAP data sources.

For organizations currently evaluating Databricks or Snowflake, SAP's enhanced platform adds another serious contender to the shortlist. The decision may increasingly come down to where an organization's most valuable data already resides — and for many enterprises, that answer is SAP.

Looking Ahead: SAP's AI Platform Ambitions Face Execution Test

SAP's acquisition strategy is bold, but execution will determine whether these moves pay off. Integrating 2 separate companies into SAP's existing product portfolio — while maintaining the open-source ethos that made Dremio popular — will require careful management.

The enterprise data platform market is expected to exceed $100 billion by 2028, according to industry estimates. SAP's move to claim a larger share of this market makes strategic sense, particularly as AI workloads drive unprecedented demand for accessible, high-quality enterprise data.

Key milestones to watch in the coming months include how quickly SAP integrates Dremio into its Business Data Cloud, whether Prior Labs' AI models appear in SAP's Joule AI assistant, and how the company prices these new capabilities for its existing customer base.

One thing is clear: SAP is no longer willing to sit on the sidelines while cloud-native startups redefine how enterprises manage and analyze their data. With these acquisitions, the 52-year-old software giant is making its most consequential bet on the AI era — and the enterprise data platform market will never look the same.