Dremio Advances Lakehouse Intelligence – Reinvents the Data Warehouse for the AI Era

Latest advancements enable organizations to quickly operationalize AI

Iceberg Summit, SAN FRANCISCO, Calif., April 08, 2025 (GLOBE NEWSWIRE) — Dremio, the Intelligent Data Lakehouse Platform, today announced the availability of its latest release, marking the next generation of Dremio with breakthrough intelligence capabilities that help organizations accelerate AI and analytics projects, and reduce costs. Announced at Iceberg Summit 2025, the new Autonomous Reflections, Iceberg Clustering, AI-enabled Semantic Search, and enhancements to the Enterprise Catalog eliminate manual performance tuning and simplify data discovery. 

By reducing technical complexity and resource waste through intelligent automation, Dremio liberates teams to innovate, all while strengthening data governance. To learn more visit here or join us at the Iceberg Summit here.

“Organizations need a modern data foundation that can support both traditional analytics and emerging AI workloads, as legacy approaches are often too rigid, complex, or costly to scale,” said Marlanna Bozicevich, research analyst at IDC. “Dremio’s newest release addresses these challenges by combining autonomous optimization with open architecture to democratize data access. This enables organizations to build a future-proof data foundation for both analytics and AI initiatives.”

The Only Lakehouse with Autonomous Performance

With less time spent tuning performance, optimizing tables, and creating pre-calculated tables and extracts, data engineers can focus on delivering high-quality datasets that power agentic applications. Dremio’s highly innovative technology leverages intelligence to deliver on this promise:

• Autonomous Reflections — An industry-first innovation developed by Dremio — automatically optimizes performance while ensuring queries run on live, up-to-date data with no SQL changes. Autonomous Reflections are intelligently created and updated materializations based on query patterns that act like a persistent, always-fresh cache. The technology eliminates time-consuming manual performance tuning, delivers sub-second queries for all AI and BI workloads, and significantly reduces compute costs.
• Iceberg Clustering — the industry’s first data clustering offering for Iceberg — brings automated data layout optimization to Apache Iceberg lakehouses. With Iceberg clustering, Dremio eliminates the need to partition tables, delivering dramatically faster queries and lower compute costs without any manual effort or tuning. 

Rapidly Create AI-Ready Data Sets
Most AI initiatives are bottlenecked by delivering AI-ready datasets, and the biggest factors include unifying data, developing a semantic layer, and then discovering the data needed to support the business initiative. Dremio is currently used by thousands of companies to develop a unified semantic layer, and with its next-generation release it’s leveraging AI to make discovery across tables and sources easier and faster than ever.  

• AI-enabled Semantic Search reduces data discovery time from days to seconds, even within complex data environments. Faster data discovery significantly accelerates AI and analytics initiatives by making it simple for users and AI agents to discover existing data assets across an enterprise’s entire data estate using plain business language. It also removes the need for SQL experience and/or technical expertise. 

Open and Flexible Iceberg Architecture
The AI era demands an interoperable architecture that makes it simple to leverage new innovations from both established and new organizations as well as open source projects.  Apache Iceberg^TM, the standard open table format, and Apache Polaris^TM (Incubating), the standard Iceberg catalog, provide the open foundation for interoperability. Dremio is the first to provide an enterprise catalog powered by Apache Polaris that can be run in any cloud or on-premises environment. 

• Open Architecture with Polaris Catalog expands its open and governed foundation with enhancements to Dremio’s enterprise catalog powered by Apache Polaris , a fully Iceberg-native metastore. Polaris provides fine-grained access controls, robust data lineage, and deep governance capabilities across all workloads. As part of the open Iceberg ecosystem, Polaris enables seamless interoperability across engines and tools, empowering organizations to future-proof their data architecture with flexibility, transparency, and control.

“Apache Iceberg is proof of what can happen when users from a variety of backgrounds and different goals all get together to build software. The interoperability of the Iceberg format has allowed it to be successful in an industry full of options for working with big data,” said Russell Spitzer, Apache Polaris (Incubating) PPMC, Apache Iceberg PMC, and Principal Software Engineer at . “Apache Polaris (Incubating) is that next step towards data interoperability, and perfectly fits the missing niche of a project that is contributed to by a variety of engineers aiming for vendor-neutrality and interoperability first. The donation of the project to the Apache Software Foundation shows real action working towards those goals and Snowflake is excited to stand with Polaris on its journey.”

“Empowering our customers with robust data governance on STACKIT is crucial,” said   Benjamin Schweizer Senior Manager, Domain Product Owner, STACKIT – Central Services. “The Dremio Enterprise Catalog provides a secure central platform to manage data and ensures full data sovereignty within the trusted STACKIT Cloud.”

Together, Dremio’s latest capabilities form a unified, open, and intelligent lakehouse that uniquely enables organizations to accelerate their AI and analytics initiatives.

“The paradox today is clear: AI demands massive amounts of high-quality data, yet teams are being asked to do more with less,” said Tomer Shiran, founder of Dremio. “Our Spring 2025 release resolves this tension by eliminating the bottlenecks slowing teams down. With Autonomous Reflections and Iceberg Clustering, data teams no longer have to worry about query performance. With Apache Polaris, AI-Enabled Semantic Search, and an MCP interface, AI agents and other data consumers can instantly find what they need. We’re transforming how enterprises deliver data for AI initiatives. No other platform provides this combination of speed, governance, and flexibility.”

About Dremio
Dremio is the intelligent lakehouse platform trusted by thousands of global enterprises like Amazon, Unilever, Shell, and S&P Global. Dremio amplifies AI and analytics initiatives by eliminating the significant and time-intensive process of dataset creation. Designed to help data engineering teams who are already overburdened with disconnected data sources and prolonged iteration cycles with business stakeholders that slow progress, Dremio eliminates bottlenecks by unifying data sources without ETL, simplifying the creation of high-quality, governed datasets, and delivering autonomous performance optimization to accelerate AI. Developed by the original creators of Apache Polaris and Apache Arrow, Dremio is the only lakehouse built natively on Apache Iceberg, Polaris, and Arrow – providing flexibility, preventing lock-in, and enabling community-driven innovation. To learn more visit www.Dremio.com.

CONTACT: Elise Woodard
Dremio Corporation
9494632203
elise.woodard@dremio.com