Dremio Unveils Across-the-Board Improvements to Data Lakehouse Platform
Dremio used today’s Iceberg Summit as the venue to unleash across-the-board improvements to its data lakehouse platform, including enhancements for data management that will resonate with organizations pursuing anything from analytics to generative AI.
Intelligent Data Lakehouse Platform
Dremio has morphed over the years from a developer of an open source SQL query engine to a full-stack provider of a data lakehouse. Its Intelligent Data Lakehouse Platform combines its query engine with a data storage environment based on Apache Iceberg, the innovative open table format developed at Netflix and Apple to solve data consistency issues in Hadoop clusters.
New Capabilities
The enhancements that Dremio unveiled today with its Spring 2025 release address several issues and use cases that are impacting its customers, ranging from data management and SQL analytics to ensuring performance of AI applications.
- Autonomous Reflections: A new capability that will function as a materialized cache that is always kept up-to-date with the latest data. Dremio says this cache will provide sub-second queries for AI and SQL queries and eliminate the need for manual performance tuning while cutting compute costs.
- Iceberg Clustering: Automatically delivers optimized data layouts for Iceberg lakehouses. Iceberg Clustering will improve query speeds while eliminating the need to partition tables, the company says.
AI and Data Management
Kevin Petrie, vice president of research at BARC US, says Dremio’s moves will help customers’ AI projects.
"Many popular AI use cases, including chatbots, recommendation engines and anomaly detection, require simple real-time access to structured or semi-structured data," Petrie said. "Dremio gets positive reviews for meeting these requirements for ease of use and performance, and this announcement further strengthens those capabilities."
Metadata Catalog
Dremio’s Spring 2025 release also introduces support for Apache Polaris, the open source metadata catalog introduced by Snowflake last year, in Dremio’s enterprise metadata catalog offering.
Polaris, which is currently incubating at the Apache Software Foundation, provides fine-grained data access controls and data lineage-tracking capabilities for Iceberg tables, and serves as the interface for query engines that want to access Iceberg data in lakehouses. Dremio says it is the first vendor to provide a Polaris-powered metadata catalog that can run in any cloud or on-premise environments.
Semantic Search
Dremio also launched a new AI-enabled semantic search capability that it says will reduce data discovery time from days to just seconds. It says the new search function will eliminate the need for technical skills or advanced SQL knowledge to discover existing data, either by humans or AI agents.
Conclusion
Dremio’s Spring 2025 release resolves the paradox of AI demanding massive amounts of high-quality data while teams are being asked to do more with less. By eliminating the bottlenecks slowing teams down, Dremio is transforming how enterprises deliver data for AI initiatives.
FAQs
Q: What are the new capabilities introduced by Dremio’s Spring 2025 release?
A: The new capabilities include Autonomous Reflections, Iceberg Clustering, support for Apache Polaris metadata catalog, and AI-enabled semantic search.
Q: How will Autonomous Reflections benefit AI and SQL queries?
A: Autonomous Reflections will provide sub-second queries for AI and SQL queries and eliminate the need for manual performance tuning while cutting compute costs.
Q: What is Apache Polaris metadata catalog?
A: Apache Polaris metadata catalog is an open source metadata catalog introduced by Snowflake last year, which provides fine-grained data access controls and data lineage-tracking capabilities for Iceberg tables.
Q: How will Dremio’s metadata catalog support Apache Polaris?
A: Dremio’s metadata catalog will support Apache Polaris, making it the first vendor to provide a Polaris-powered metadata catalog that can run in any cloud or on-premise environments.
