The Dremio Blog

Large Language Models (LLMs) are capable of understanding and generating language. However, they do not understand or process language in the same way that a person like you or I does.  When reading text, humans construct meaning by processing the syntax of each sentence as it unfolds. This involves combining word definitions, using context from […]

Discover the top AI tools for data engineers. Compare leading platforms and see how Dremio automates pipelines and boosts performance at scale.

Explore 18 strategies for optimizing SQL queries and learn how enterprises improve speed, reduce compute costs, and maintain efficient workloads with Dremio.

Discover how AI-ready data drives accuracy, scalability, and efficiency—and how Dremio’s Intelligent Lakehouse simplifies the entire process.

These four capabilities are not just a list of features; they are a reinforcing system. The semantic layer provides the context, federation provides the reach, autonomous optimization delivers the speed, and the MCP framework enables the final, crucial step: action. This is the complete blueprint for agentic analytics.

Companies are racing to operationalize agentic AI, yet the final process of getting from data to decision is extremely difficult,  requiring data integration, tuning, and governance management. With Dremio’s latest release, we remove these blockers by putting natural‑language intelligence, explainability, and self‑optimizing performance directly into the lakehouse experience. You get clarity and control without copies, […]

Dremio has introduced several capabilities that inteliigently improve query performance across the data lakehouse. With minimal to no action from users, Dremio will reduce query latency, handle data maintenance tasks, and eliminate redundant compute jobs. This article is a summary of three of these performance management features. Read on to learn how reflections accelerate popular […]

The Intelligent Lakehouse for the Agentic AI Era Data teams today face a familiar challenge: how to unlock value from ever-growing, scattered data without the delays and cost of traditional ETL pipelines. Together, HPE Alletra Storage MP X10000 and Dremio’s Intelligent Lakehouse Platform solve this problem—combining HPE’s flash-optimized performance with Dremio’s open, unified query and […]

Dremio is always striving to abstract away the physical concerns of data, whether the storage location, partitioning schema, or file size optimisation. Thanks to features such as Data Federation, Iceberg Clustering, and Autonomous Performance functionalities, Dremio users get highly-performant access to their data no matter where it lives.  One of the components that delivers this […]

The New Economics of Data Cloud data warehouses like Amazon Redshift were built for a world that no longer exists. In that earlier era, organizations focused primarily on structured business intelligence, static dashboards, and predictable workloads. Data was tightly controlled, compute resources were fixed, and dynamic scalability for rapidly changing workloads was not a concern. […]

Caching dramatically reduces latency and computational costs by storing frequently accessed data closer to where it's needed. Instead of repeated expensive operations - such as fetching from object storage, planning complex queries, or executing SQL - the data you need is provided in fast, local memory. To deliver on this, Dremio implements different layers of […]

The Shift from Warehouses to the Agentic Lakehouse Amazon Redshift has long been a dependable data warehouse for analytics, but the analytics landscape has evolved. Organizations are no longer just running dashboards—they’re powering agentic AI systems that reason, act, and make autonomous decisions based on live business data. These workloads demand real-time responses, high concurrency, […]

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Overview Dremio provides out-of-the-box methods of handling complex data types in, for example JSON and parquet datasets. Common characteristics are embedded “columns within columns” and “rows within columns”.  In this blog, we will demonstrate how Dremio can discover and handle these types of data. The examples have been tested on the following Dremio versions: Preparation […]

Agentic AI is an artificial intelligence system that is designed to operate autonomously. With minimal human supervision it can be expected to make decisions and perform tasks with specifically trained agents. This is thanks in large part to Large Language Models (LLMs) which provide agentic AI with enhanced reasoning and the ability to understand context. […]