The Dremio Blog

Moving data from source systems like MySQL to a dashboard traditionally involves a multi-step process: transferring data to a data lake, moving it into a data warehouse, and then building BI extracts and cubes for acceleration. This process can be tedious and costly. However, this entire workflow is simplified with Dremio, the Data Lakehouse Platform. Dremio enables you to directly serve BI dashboards from MySQL or leverage Apache Iceberg tables in your data lake.

Moving data from source systems like Elasticsearch to a dashboard traditionally involves a multi-step process: transferring data to a data lake, moving it into a data warehouse, and then building BI extracts and cubes for acceleration. This process can be tedious and costly. However, this entire workflow is simplified with Dremio, the Data Lakehouse Platform. Dremio enables direct serving of BI dashboards from Elasticsearch or leveraging Apache Iceberg tables in your data lake.

By leveraging a lakehouse architecture, organizations can achieve significant savings on storage and compute costs, streamline transformations with virtual modeling, and enhance data accessibility for analysts and scientists.

The Dremio Unified Analytics Platform for Analytics and AI hosted our 6th Annual Subsurface Live event this week - the only event dedicated to Lakehouse learning. We are excited to share a few of the exciting announcements, developments, and new capabilities! Dremio for Every Environment Dremio has always been the most flexible lakehouse deployment, with […]

ical use cases. While you can deploy Dremio as self-managed software in a Kubernetes environment, you can get some nice bonuses when working with a Dremio Cloud Managed environment

PuppyGraph's sponsorship underlines our dedication to empowering individuals and organizations with knowledge and tools to navigate and excel in the evolving data landscape. Through its innovative platform and active participation in the community, PuppyGraph continues to lead the way in advancing graph analytics and data lakehouse technologies, making the complexities of big data more accessible and manageable.

By sponsoring the Subsurface Conference, we aim to connect with the community, share insights, and explore the future of data lakehouses together. Join us at the conference to witness the evolution of data management and take your first step towards an optimized data future with Apache Iceberg and Upsolver.

Tim Hurski, Prashanth Badari, Sonal Chavan, Dexin Zhu and Dmitry Chirkov

Dremio's version 25 is not just an update; it's a transformative upgrade that redefines the standards for SQL query performance in lakehouse environments. By intelligently optimizing query processing and introducing user-friendly features for data management, Dremio empowers organizations to harness the full potential of their data, driving insightful business decisions and achieving faster time-to-value. With these advancements, Dremio continues to solidify its position as a leader in the field of data analytics, offering solutions that are not only powerful but also practical and cost-effective.

Dremio version 25 represents a significant leap forward in making lakehouse analytics more accessible and manageable. With its enhanced monitoring capabilities, seamless third-party integrations, and a suite of additional features, Dremio is setting a new industry standard for ease of administration. These improvements streamline the monitoring process and empower administrators to proactively manage their environments, ensuring that Dremio continues to be an optimal choice for companies seeking advanced, user-friendly analytics solutions.

Dremio's version 25 is not just an incremental update; it's a transformative release that redefines stability and durability in SQL analytics. By introducing sophisticated memory management, spillable hash joins, and a proactive memory arbiter, Dremio ensures businesses can rely on its engine for their most critical and complex data workloads.

With version 25, Dremio redefines the analytics landscape for Apache Iceberg, offering a robust, efficient, and user-friendly platform. By enhancing its native support for Iceberg and integrating features like real-time data ingestion and simplified migration, Dremio empowers organizations to harness the full potential of their data, enabling insightful analytics and informed decision-making in a modern data environment.

Dremio serves as a bridge, connecting data from diverse sources and making it accessible across various platforms. In tandem with Upsolver, we can establish continuous data pipelines that ingest streaming data from sources like Apache Kafka or Amazon Kinesis, depositing this data into Iceberg tables within our AWS Glue catalog. This setup empowers Dremio to perform real-time analytics, creating a potent synergy that yields impactful outcomes.

With the latest release of Dremio, 25.0 we are helping accelerate the adoption and benefits of Apache Iceberg, while  bringing  your users closer to the data with lakehouse flexibility, scalability and performance at a fraction of the cost.  We are excited to announce some of the new features that improve scalability, manageability, ease of use […]

Dremio's unwavering commitment to Apache Iceberg is not merely a strategic choice but a reflection of our vision to create an open, flexible, and high-performing data ecosystem. Our deep integration with Apache Iceberg throughout the entire stack complements Dremio's extensive functionality, empowering users to document, organize, and govern their data across diverse sources, including data lakes,  data warehouses, relational databases and NoSQL tables. This synergy forms the bedrock of our open platform philosophy, facilitating seamless data accessibility and distribution across the organization.