Introduction
SAP recently announced its intention to acquire Dremio, a company that positions itself as an agentic lakehouse provider, for an undisclosed sum. This move introduces complexity given that SAP already partners with established data platforms like Snowflake and Databricks. However, industry analysts highlight key differentiators: Dremio’s ability to query and manage data that remains within an enterprise’s own environment, rather than requiring data to be moved externally. This acquisition aligns with SAP’s goal of simplifying the integration of SAP and non-SAP data, and more critically, of making complex datasets AI-ready.
Why Dremio? Addressing Data Fragmentation for AI
SAP’s primary justification for the acquisition centers on easing the burden on IT executives who grapple with combining SAP data with data from other sources. A more compelling rationale lies in Dremio’s potential to transform messy, fragmented data into a format fit for artificial intelligence—quickly and cost-effectively. In its announcement, SAP noted: “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. Dremio helps eliminate that data fragmentation and integration friction.” Yet, experts caution that Dremio alone cannot solve all data quality issues—such as outdated information, unreliable sources, or lack of context—which remain challenges for any enterprise.
The Apache Iceberg‑Native Lakehouse Vision
SAP plans to integrate Dremio into its Business Data Cloud, creating an Apache Iceberg‑native enterprise lakehouse. Apache Iceberg, an open table format, will serve as the foundation, enabling SAP and non-SAP data to coexist without any data movement or format conversion. This approach promises “federated analytical reach across every enterprise data source,” meaning organizations can maintain data in place while still gaining unified insights.
How Dremio Stacks Up Against Snowflake and Databricks
The comparison between Dremio and incumbent partners Snowflake and Databricks is nuanced. Dremio is a younger, less established player, which as analysts point out may not yet match the enterprise readiness of its competitors. Snowflake and Databricks offer mature, multi‑cloud platforms with robust security features. However, Dremio’s acquisition price is likely far lower than what either Snowflake or Databricks would command today, making it a more affordable strategic bet for SAP. Furthermore, Dremio’s unique selling point—working with data where it resides—could appeal to organizations wary of vendor lock‑in or data egress costs.
Analyst Perspectives on Maturity and Security
Harikishore Sreenivasalu, CEO of Aarini Consulting, notes that while Snowflake and Databricks have mature, enterprise‑ready platforms, “Dremio is the new entrant in the market and they have to mature more to be enterprise ready. Their security aspects need to mature.” Still, he acknowledges that the situation could evolve after the acquisition, as SAP brings resources and expertise to accelerate Dremio’s development.
Conclusion: A Bet on an Open, AI‑Ready Future
By acquiring Dremio, SAP is making a clear bet on an open‑format lakehouse strategy that reduces data movement and lowers the barrier to AI adoption. While Dremio may not yet match the maturity of Snowflake or Databricks, its unique capabilities and the backing of SAP could quickly close the gap. For enterprises already invested in SAP’s ecosystem, this acquisition promises a streamlined path to unifying data and powering agentic AI at scale.