The Dremio Blog

Dremio allows you to easily share and manage your data within your organisation, while dbt allows the teams working with that data to efficiently share and collaborate. Combining Dremio's powerful data lakehouse platform and dbt's robust data transformation capabilities allows your organisation to produce reliable and accessible data to drive decision making and power AI initiatives.

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.

A hybrid lakehouse strategy offers the best of both worlds—leveraging the scalability of the cloud and the control of on-premises infrastructures. By addressing the limitations of cloud-only solutions, hybrid lakehouses enable organizations to optimize costs, enhance performance, and ensure robust governance.

As 2024 comes to a close, it’s clear that this year has been remarkable for the data lakehouse and the growing momentum driving its adoption. In this blog, I’ll reflect on some of the most exciting developments in the data lakehouse space, focusing on the new possibilities unlocked by tools like Apache Iceberg and Dremio.

Business data needs are quickly evolving, and technology is adapting to keep pace. Cloud data warehouses now offer elastic storage and compute. Data lakes have evolved into lakehouses, combining lakes' flexibility with warehouses' reliability. Many organizations are utilizing a hybrid on-prem + cloud data storage strategy. Transformation tools have shifted from proprietary ETL platforms to open-source frameworks that enable software engineering practices on analytics. These technological advances are fundamentally changing how organizations work with data.

Welcome to the 2024 Football Playoffs Hackathon powered by Dremio. Teams from across the globe will apply their analytics prowess to predict:  American Champion National Champion Overall League Winner Each team must analyze current stats provided to support their selections with detailed insights.  Judging criteria will include the accuracy of predictions, the quality of analysis, the clarity of visual presentation, and the depth of insights shared.

Traditional data management techniques increasingly struggle to keep pace with modern data's volume, variety, and velocity. The need to evolve legacy data management to enable AI-ready data has caused organizations to evaluate their data strategies. Two innovative approaches have gained prominence: Data Mesh and Data Fabric.

Dremio’s unique features and integrations make it the ultimate SQL query engine for Apache Iceberg tables. Its industry-leading raw performance, innovative query acceleration with Reflections, and powerful catalog options provide a seamless experience for managing and querying Iceberg tables across diverse data environments. These capabilities ensure you can handle modern analytics workloads quickly, consistently, and easily.

With Dremio, organizations can unify their data landscape while ensuring security and data quality, making it possible to foster a culture of data-driven decision-making at every level.

For enterprises ready to build a flexible, scalable, and governed data mesh, Dremio provides the ideal platform. By enabling efficient data access, documentation, and governance, Dremio ensures that every team has the tools to make data-driven decisions without compromise.

. With Dremio’s advanced metadata management, organizations can harness the full potential of their Iceberg Data Lakehouse, creating a scalable, high-performance environment that meets the demands of modern data-driven enterprises.

Through live and incremental reflection updates, Dremio enables real-time access to data in Iceberg lakehouses, ensuring fresh data for decision-making while minimizing resource consumption. Reflection hints offer a unique way to maintain data availability, even for sources that may be unreliable or resource-intensive, enhancing business continuity and user experience.

Organizations need tools that seamlessly integrate, manage, and discover data across different platforms. That’s why we’re excited to introduce the Dremio Software OCF Connector, developed by Alation. This new connector makes it easy to catalog your Dremio assets within Alation, helping teams efficiently discover, govern, and collaborate around their data.  What is the Dremio Connector […]

Finding the right platform to support and enhance Iceberg Lakehouse architecture is crucial. Dremio emerges as a must-have partner for any Iceberg journey, helping you overcome the common challenges of data migration, performance optimization, and operational complexity. By combining robust data virtualization, cost-effective infrastructure, and an integrated catalog with advanced DataOps capabilities, Dremio allows you to make the most of Iceberg’s potential while maintaining a streamlined, user-friendly data environment.

Modern organizations face a common challenge: efficiently analyzing massive datasets stored in data lakes while maintaining performance, cost-effectiveness, and ease of use. The Dremio Architecture Guide provides a comprehensive look at how Dremio's innovative approach solves these challenges through its unified lakehouse platform. Let's explore the key architectural components that make Dremio a transformative solution for modern data analytics.