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Agentic Lakehouse

Agentic Lakehouse on NetApp StorageGRID with Dremio

The joint solution from Dremio and NetApp StorageGRID addresses this challenge with a high-performance Agentic Lakehouse architecture. By combining the massive scale, durability, and efficiency of StorageGRID with Dremio's high-performance query engine, open catalog, and semantic and AI-native layers, enterprises gain direct, governed access to data where it lives.

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Agentic Lakehouse on NetApp StorageGRID with Dremio

Modern enterprises are pushing aggressively to operationalize Agentic AI and machine learning, but progress is often constrained by legacy data architectures. While object storage holds the most complete and up-to-date enterprise data, it is rarely optimized for the performance, concurrency, and semantic consistency required by AI-driven analytics and model training. The result is slow iteration, duplicated data pipelines, and fragmented intelligence across teams.

The joint solution from Dremio and NetApp StorageGRID addresses this challenge with a high-performance Agentic Lakehouse architecture. By combining the massive scale, durability, and efficiency of StorageGRID with Dremio's high-performance query engine, open catalog, and semantic and AI-native layers, enterprises gain direct, governed access to data where it lives. This open, modern foundation accelerates data-to-insight, supports high-velocity AI and analytics workloads, and removes the need for proprietary warehouses and complex ETL pipelines.

Agentic Lakehouse on NetApp StorageGRID with Dremio overview

Features and Benefits

The capabilities that set Agentic Lakehouse on NetApp StorageGRID with Dremio apart.

The Integrated Solution: An Agentic Lakehouse for StorageGRID

NetApp StorageGRID: The Scalable and Durable Data Foundation

NetApp StorageGRID is the trusted, software-defined object storage platform, providing the cost-effective, durable, and scalable foundation required for petabyte-scale AI datasets.

Dremio: The High-Performance Agentic Lakehouse

Dremio is the data lakehouse platform that transforms StorageGRID into a high-performance system for BI, SQL analytics, and demanding AI/ML workloads.

Key Advantages of the Integrated Architecture

High-Speed Analytics and Feature Engineering

Dremio's Data Reflections and Apache Arrow Engine are the key to bypassing object storage latency, delivering sub-second, interactive query performance directly on NetApp StorageGRID. This accelerated access is vital for feature engineering, the process of preparing data for ML models allowing data scientists to rapidly iterate without waiting hours for data movement or query execution.

Semantic Consistency for Enterprise AI

The Dremio Semantic Layer provides a governed, unified view of all data within StorageGRID. This ensures that the features, metrics, and definitions used for model training and business reporting are consistent, minimizing errors and improving the trustworthiness of AI outputs and business intelligence.

Maximum Cost-Efficiency and Openness

The solution leverages the extreme cost-efficiency of NetApp StorageGRID for petabyte-scale data storage combined with Dremio's open architecture. This avoids proprietary data warehouse licensing fees and significantly reduces the total cost of ownership (TCO) while offering flexibility for future data initiatives.

Key Benefits

Key Benefits

Exabyte-Scale Architecture

Effortlessly scales to accommodate massive datasets for large-scale AI model training.

Multi-Site Durability

Ensures data integrity and availability with flexible protection across geographically dispersed sites.

S3 API Compatibility

Provides a seamless interface for Dremio and other cloud-native tools, simplifying integration.

Policy-Driven Tiering

Automates data lifecycle management, optimizing costs by moving cold data to lower-cost tiers while maintaining fast access.

AI Layer

Enhances data interaction, improving performance and reducing manual effort.

Semantic Layer

Ensures data accuracy and consistency with standardized definitions.

Reflections & Query Engine

Pre-aggregates and optimizes data, delivering up to 100× acceleration and low-latency analytics.

Use Cases with Dremio and NetApp StorageGRID

Power AI Models with Fresh, Trusted Features

  • Serve features directly from object storage
  • Same logic for training and inference
  • No separate feature store to manage

Query and Understand All My Object Data Instantly

  • Run fast SQL directly on data in StorageGRID
  • No ETL, no data copies, no new warehouse
  • Same definitions and metrics for every team

Automatically Catalog and Maintain My Lakehouse Tables

  • Discover and organize tables automatically
  • Handle table maintenance and optimization for me
  • Keep schemas and data consistent as things change

One Analytics and AI Layer Across Hybrid Environments

  • Query data across on-prem and distributed sites
  • Central governance with local performance
  • No vendor lock-in or forced cloud move

Analyze Logs and Operational Data at Scale

  • Query massive log and event datasets in place
  • Build dashboards and troubleshoot faster
  • No special-purpose analytics stack required
Expert Guidance

Thrive with expert-led storage guidance

Get tailored advice on how Agentic Lakehouse on NetApp StorageGRID with Dremio fits your environment — from sizing and deployment to long-term optimization.

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Technical Specifications

Exhaustive hardware and software metrics extracted directly from official documentation.

  • Object Storage Platform
    NetApp StorageGRID
  • Lakehouse Platform
    Dremio
  • Query Engine
    Apache Arrow Engine
  • Acceleration Technology
    Data Reflections
  • API Compatibility
    S3 API

  • Architecture Scale
    Exabyte-Scale
  • Query Acceleration
    Up to 100× acceleration
  • Query Performance
    Sub-second, interactive query performance
  • Dataset Support
    Petabyte-scale AI datasets

  • Durability
    Multi-Site Durability across geographically dispersed sites
  • Tiering
    Policy-Driven Tiering
  • Semantic Layer
    Governed, unified view of all data within StorageGRID
  • AI Layer
    Enhances data interaction, improving performance and reducing manual effort

  • Document ID
    SB-4496-0326
  • Document Type
    NetApp Solution Brief
  • Copyright
    ©2026 NetApp, Inc. All Rights Reserved.

Compare Agentic Lakehouse on NetApp StorageGRID with Dremio Series

Select the right scale for your workload demands.

Model Name Max Capacity Port Config Action
NetApp StorageGRID Exabyte-Scale S3 API Compatibility Get Quote
Dremio Agentic Lakehouse Petabyte-scale AI datasets N/A Get Quote

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