Modernizing Your Hadoop Infrastructure with Dremio and NetApp
Introduction In the era of big data, organizations are increasingly recognizing the limitations of traditional Hadoop infrastructures. As data volumes grow and analytics requirements become more complex, the need for a more agile, scalable, and cost-effective solution has never been greater. Enter the data lakehouse architecture—a modern approach combining the best data lakes and data warehouses. By integrating Dremio’s cutting-edge data lakehouse platform with NetApp’s robust storage and data management solutions, enterprises can seamlessly transition from Hadoop to a more efficient, scalable, and future-ready data architecture.
The Challenges of Legacy Hadoop Environments Hadoop has long been the backbone of big data analytics for many organizations. However, as data requirements evolve, so do the challenges of managing Hadoop environments. These include:
High Costs: Maintaining large Hadoop clusters can be expensive due to hardware, software licenses, and ongoing maintenance costs.
Complex Data Management: Hadoop environments require specialized expertise to configure and maintain; overall data management can be time-consuming and error-prone.
Performance Limitations: As data volumes grow, Hadoop’s performance can degrade, leading to slower query times and reduced productivity.
Limited Flexibility: Hadoop infrastructures have tightly coupled compute and storage, which is not well-suited to the demands of modern analytical environments. This limits an organization’s ability to scale only the resources that it needs.
To address these challenges, organizations are increasingly looking to leave their Hadoop environments and migrate to a new, modern object storage-based data lakehouse architecture, which offers greater flexibility, performance, and cost efficiency.
Introducing Dremio and NetApp: A Winning Combination for Hadoop Modernization Dremio, a Unified Lakehouse Platform for Self-Service Analytics, enables organizations to perform high-performance analytics directly on data lakes. Dremio’s powerful SQL query engine, combined with its ability to integrate seamlessly with existing data infrastructure, makes it the ideal solution for organizations looking to modernize their Hadoop environments. NetApp, a leader in data management and storage solutions, offers a suite of products designed to deliver unmatched performance, scalability, and simplicity. With NetApp’s StorageGRID solution, organizations can efficiently manage and scale their data storage, ensuring that their data is always available, secure, and ready for analysis. Together, Dremio and NetApp provide a comprehensive solution for Hadoop modernization, allowing organizations to migrate their data and analytics workloads to a modern, scalable, and cost-effective Hybrid Iceberg Lakehouse architecture.
Key Benefits of the Dremio and NetApp Hybrid Lakehouse Solution
Seamless Data Migration Migrating from Hadoop to a modern data architecture can be daunting. However, Dremio’s support for Hadoop enables organizations to seamlessly transition from their legacy environment to their new, modern Hybrid Iceberg Lakehouse based on NetApp StorageGRID object storage. Users can access and query data in both environments as the transition occurs, eliminating downtime and any interruption in analytical processes.
High-Performance Analytics Combining Dremio’s advanced query engine and NetApp’s high-performance storage solutions ensures that organizations can achieve sub-second query response times, even on large datasets. This enables real-time analytics, empowering data teams to make faster, more informed decisions.
Self-Service Dremio's self-service capabilities empower data consumers by providing direct, intuitive access to data without IT intervention. With Dremio’s powerful semantic layer and user-friendly interface, analysts and data scientists can easily explore, curate, and analyze data across multiple sources in real-time. This democratization of data enables faster decision-making and reduces the dependency on data engineering teams, enhancing overall business agility.
Scalability and Flexibility NetApp’s scalable storage solution, StorageGRID, allows organizations to scale their data storage infrastructure as their needs evolve easily. Dremio’s Unified Lakehouse Platform complements this by scaling vertically and/or horizontally to meet any user, query, or data volume requirements, providing the flexibility needed to adapt to rapidly changing business requirements.
Simplified Data Management Dremio’s robust data management and governance capabilities enable businesses to easily and efficiently manage vast amounts of data within their lakehouse environments. Dremio’s Lakehouse Management provides a robust enterprise Iceberg catalog, Git-inspired versioning, automated data optimization, and numerous other features that simplify data management. With NetApp StorageGRID’s powerful data management features, such as the dynamic policy engine that supports information lifecycle management (ILM) rules, organizations can automate many of the complex tasks associated with managing large data environments. This reduces the burden on IT teams, allowing them to focus on more strategic initiatives.
Cost Efficiency By migrating to a modern Hybrid Iceberg Lakehouse architecture with Dremio and NetApp, organizations can reduce the spending tied to costly Hadoop licenses. At the same time, by separating compute and storage, organizations can scale only the resources they need, decreasing the total cost of ownership. Dremio’s Unified Lakehouse Platform and NetApp’s StorageGRID provide a cost-effective alternative to traditional Hadoop data lake infrastructures, allowing organizations to do more with less.
Getting Started with Dremio and NetApp The integration of Dremio and NetApp provides a powerful solution for organizations looking to modernize their Hadoop environments and unlock the full potential of their data. Whether your goal is to improve query performance, simplify data management, or reduce costs, Dremio and NetApp offer the tools you need to succeed.
Want to learn more about how Dremio and NetApp can help transform your Hadoop infrastructure?
Hadoop Modernization on AWS with Dremio: The Path to Faster, Scalable, and Cost-Efficient Data Analytics
Hadoop modernization on AWS with Dremio represents a significant leap forward for organizations looking to leverage their data more effectively. By migrating to a cloud-native architecture, decoupling storage and compute, and enabling self-service data access, businesses can unlock the full potential of their data while minimizing costs and operational complexity.
Nov 26, 2025·Dremio Blog: Partnerships Unveiled
Using Dremio, lakeFS & Python for Multimodal Data Management
With lakeFS, you version everything: Iceberg tables, images, models, logs. With Dremio, you query and analyze it all, structured or not, at scale. Together, they bring Git-style control and interactive querying to your data lake, so you can build more intelligent, version-aware workflows without sacrificing flexibility or performance.
Jun 11, 2019·Dremio Blog: Partnerships Unveiled
What is ADLS Gen2 and Why it Matters
Described by Microsoft as a “no-compromise data lake”, ADLS Gen 2 extends the capabilities of Azure Blob Storage and is optimized for large scale analytics workloads.