The Dremio Blog

In today’s data-driven world, businesses face the constant challenge of managing and analyzing data across various environments—cloud, on-premises, and hybrid. With our latest release of Dremio 25.1, we continue to innovate and deliver features that enhance performance, streamline data ingestion, and improve federated query access. This release introduces improvements that collectively drive better performance, efficiency, […]

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.

As organizations continue to navigate the complexities of modern data environments, Dremio’s self-service capabilities offer a clear path forward, allowing businesses to unlock the full value of their data assets while maintaining control and governance. With Dremio, the future of self-service analytics is not just achievable—it’s within reach.

Apache Iceberg has an expansive ecosystem, and this article provides an overview of eight powerful tools that can facilitate data ingestion into Apache Iceberg and offers resources to help you get started. Whether leveraging Dremio's comprehensive lakehouse platform, using open-source solutions like Apache Spark or Kafka Connect, or integrating with managed services like Upsolver and Fivetran, these tools offer the flexibility and scalability needed to build and maintain an efficient and effective data lakehouse environment.

The evolution of data storage—from the simplicity of CSV and JSON to the efficiency of Parquet and the advanced capabilities of Apache Iceberg—reflects the growing complexity and scale of modern data needs. As organizations progress through this journey, the Dremio Lakehouse Platform emerges as a crucial ally, offering seamless query capabilities across all these formats and ensuring that your data infrastructure remains flexible, scalable, and future-proof. Whether you're just starting with small datasets or managing a vast data lakehouse, Dremio enables you to unlock the full potential of your data, empowering you to derive insights and drive innovation at every stage of your data journey.

Modernizing a Hadoop data lake with Dremio and MinIO brings substantial advantages to organizations seeking to enhance their data infrastructure. This transformation not only resolves the performance, scalability, and cost challenges associated with traditional Hadoop environments but also empowers businesses to achieve greater agility and efficiency. By leveraging Dremio's advanced analytics capabilities and MinIO's scalable storage, companies can modernize their data lakes to meet the demands of today's fast-paced, data-driven world. The result is a robust, flexible, and cost-effective data environment that accelerates time to market and drives business innovation.

The Iceberg Data Lakehouse represents a significant advancement in data management architectures, combining the best features of data lakes and data warehouses. Its robust features, scalability, and cost efficiency make it a compelling choice for organizations looking to optimize their data platforms. Learn more about Lakehouse management for Apache Iceberg and why there's never been a better time to adopt Apache Iceberg as your data lakehouse table format.

Maintaining an Apache Iceberg Lakehouse involves strategic optimization and vigilant governance across its core components—storage, data files, table formats, catalogs, and compute engines. Key tasks like partitioning, compaction, and clustering enhance performance, while regular maintenance such as expiring snapshots and removing orphan files helps manage storage and ensures compliance. Effective catalog management, whether through open-source or managed solutions like Dremio's Enterprise Catalog, simplifies data organization and access. Security is fortified with Role-Based Access Control (RBAC) for broad protections and Fine-Grained Access Controls (FGAC) for detailed security, with tools like Dremio enabling consistent enforcement across your data ecosystem. By following these practices, you can build a scalable, efficient, and secure Iceberg Lakehouse tailored to your organization's needs.

Apache XTable offers a way to convert your existing data lakehouse tables to the format of your choice without having to rewrite all of your data. This, along with robust Iceberg DML support from Dremio, offers an additional way to easily migrate to an Apache Iceberg data lakehouse along with the catalog versioning benefits of the Dremio and Nessie catalogs.

Migrating to an Apache Iceberg Lakehouse enhances data infrastructure with cost-efficiency, ease of use, and business value, despite the inherent challenges. By adopting a data lakehouse architecture, you gain benefits like ACID guarantees, time travel, and schema evolution, with Apache Iceberg offering unique advantages. Selecting the right catalog and choosing between in-place or shadow migration approaches, supported by a blue/green strategy, ensures a smooth transition. Tools like Dremio simplify migration, providing a uniform interface between old and new systems, minimizing disruptions and easing change management. Leveraging Dremio's capabilities, such as CTAS and COPY INTO, alongside Apache XTable, ensures an optimized and seamless migration process, maintaining consistent user experience and robust data operations.

The Dremio and NetApp partnership represents a significant advancement in data management and analytics. By integrating NetApp StorageGRID with Dremio's data lakehouse platform, organizations can achieve unparalleled performance, scalability, and efficiency in their data operations. This powerful combination empowers enterprises to unlock the full potential of their data, driving innovation and growth in today's competitive landscape.

In previous blogs, we've discussed understanding Polaris's architecture and getting hands-on with Polaris self-managed OSS; in this article, I hope to show you how to get hands-on with the Snowflake Managed version of Polaris, which is currently in public preview.

By implementing Dremio, you can transform your existing data lakes into efficient, high-performing, and easily manageable data lakehouses. Whether you aim to modernize your infrastructure, facilitate seamless migrations, or create a hybrid data environment, Dremio provides the tools and capabilities to achieve your business goals.

Whether you're dealing with massive datasets, complex data environments, or the need for real-time analytics, the MinIO and Dremio hybrid lakehouse provides the perfect solution. It's an investment in future-proofing your data infrastructure, driving innovation, and unlocking new business opportunities. Make the smart choice today and transform your data strategy with MinIO and Dremio.

In the modern, data-driven landscape, efficient data storage, management, and analysis are essential for staying competitive. The VAST Data Platform, with its innovative architecture and comprehensive features, provides a powerful solution for data-intensive computing. When combined with Dremio, in a data lakehouse solution, companies can unlock the full potential of their data, accelerating insights, decision-making, and ensuring cost efficiency and security. Leveraging the combined power of VAST Data and Dremio, companies can transform their data into actionable knowledge, enabling them to lead with vision and innovation.