The Dremio Blog

Explore the factors that impact the average cost of a data warehouse, learn pricing models, and discover strategies to optimize your annual spend.

Explore the top data lakehouse solutions for 2026 and discover why Dremio is the best option for users who need cost-efficient, enterprise-grade performance.

Last week I published a blog about some of the risks to consider when implementing Agentic AI in your workflows or organisation. But what about the other side of that coin, the benefits this revolutionary technology can bring about? Read on to learn several of the ways that Agentic AI is transforming how we work […]

Agentic AI offers several compelling benefits that are transforming how we work and solve problems. The key difference from traditional AI is agency, the agent’s ability to plan, use tools, take actions in sequence, and work toward goals rather than just responding to individual prompts. There are many upsides to embracing AI agents in your […]

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 […]