The Dremio Blog

The traditional barriers between complex, distributed data and clear, actionable answers have been removed. With an intelligent, AI-native data lakehouse, you no longer need to be a data engineer to explore your data; you just need to be curious.

Dremio Reflections don't just accelerate queries; they accelerate the entire analytics lifecycle by removing performance tuning from the critical path. By reclaiming the time and cognitive overhead traditionally spent on manual materialization management, Reflections empower data teams to shift their focus from infrastructure management to insight delivery.

The semantic layer has evolved far beyond its origins as a simple data dictionary. This evolution is marked by five critical shifts: a scalable layered architecture, a focus on serving AI as a primary consumer, a hybrid virtual-physical model for performance, universal federation into a single pane of glass, and governance that is built-in, not bolted-on. It now serves as the critical interface not just for human analysts using BI tools, but for a new generation of AI agents that rely on its rich semantic context to explore, analyze, and generate insights from data.

A truly modern data lakehouse is defined by more than just its use of open formats. Its value is measured by its intelligence and completeness. It is a platform where AI can take action, where openness extends to other compute engines, where the semantic layer is a structured and programmable asset, and where performance management is autonomous. These integrated capabilities are shifting the baseline for what organizations should expect from a data platform. The focus is no longer just on storing and querying data, but on creating a self-managing, intelligent, and truly unified ecosystem. As you evaluate your data strategy, ask yourself a forward-looking question: As AI becomes a more active participant in our data ecosystems, how will you leverage it to not just analyze your business, but to help run it?

Dremio's AI Functions are more than just a new feature; they are a bridge over the long-standing divide between unstructured data and SQL-based analytics. By embedding LLM capabilities directly into the query engine, Dremio provides a complete workflow to unlock your most inaccessible data. You can now analyze data where it lives, choose the best AI model for the job, manage workloads with enterprise-grade controls, and transform raw files into governed, high-performance data products. The era of inaccessible information is over.

The data lakehouse is evolving beyond just being a repository for data. With Dremio, it's becoming an autonomous, open, and intelligent platform that actively works to simplify your architecture, accelerate your queries, and expand the very definition of what data can be analyzed.

We're excited to announce the introduction of Service Users in Dremio—a new authentication approach designed specifically for the agentic AI era, supporting machine-to-machine (M2M) applications and automated systems. Service users provide a more secure and streamlined way to integrate AI agents,  applications, scripts, and CI/CD pipelines with your Dremio environment. What Are Service Users? Service […]

We’re excited to share, in partnership with Microsoft, that Dremio is the first agentic lakehouse platform to fully support the open source Apache Arrow Database Connectivity (ADBC) driver for Power BI, bringing next-generation performance to your analytics. Whether you’re working with Dremio Cloud or Dremio Software, this enhancement is available across Power BI Desktop, Power […]

In this blog you will learn how to connect each tool to a REST catalog like Dremio Catalog, using bearer tokens and vended credentials to keep your pipelines secure and portable.

Dremio Next Gen Cloud represents a major leap forward in making the data lakehouse experience seamless, powerful, and accessible. Whether you're just beginning your lakehouse journey or modernizing a complex data environment, Dremio gives you the tools to work faster and smarter—with native Apache Iceberg support, AI-powered features, and a fully integrated catalog. From federated queries across diverse sources to autonomous performance tuning, Dremio abstracts away the operational headaches so you can focus on delivering insights. And with built-in AI capabilities, you're not just managing data—you’re unlocking its full potential.

We’re excited to announce Dremio Cloud, The Agentic Lakehouse—the lakehouse built for agents and managed by agents. This milestone marks a major leap forward in Dremio’s evolution, reimagining the modern lakehouse for the agentic era, where intelligent systems collaborate with humans to deliver insights, automate operations, and continuously optimize performance. As organizations accelerate their AI […]

Many data engineers and data analysts spend much of their day in Visual Studio (VS) Code, writing SQL, testing queries, and working with data. Constantly switching between tools disrupts productivity and the user work flow. The VS Code extension for Dremio brings the power of the agentic lakehouse directly into your development environment, enabling you […]

Companies are racing to operationalize agentic AI, but the path from raw unstructured data to an informed decision often breaks down in the final mile. Teams juggle schema knowledge, joins, query tuning, visualization tools, and unified governance checks before they can answer even a simple business question. With Dremio’s Agentic Lakehouse, we remove that friction […]

The rapid growth of the use of AI throughout the modern data stack has transformed how organizations extract insights from their data. With our latest release, we're excited to announce the general availability of AI Functions — a capability that brings the power of Large Language Models (LLMs) directly into SQL execution, making Dremio’s Agentic […]

Discover how Dremio’s Next Generation Cloud and enterprise MCP Server simplify data exploration with AI-driven queries, governance, and natural-language SQL.