The Dremio Blog

Building an agentic lakehouse with Dremio moves your organization beyond the "phone book" catalog of the past and into a future where the catalog is a dynamic knowledge base.

Agentic analytics isn’t a trend. It’s the next phase of how organizations work with data. AI agents need access, speed, and context, across every system your business relies on.

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.

Taken together, these changes show a project that is tightening its foundations while expanding its scope. Polaris 1.3.0 improves visibility through metrics, strengthens governance through externalized policy, and broadens catalog coverage through generic tables.

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 […]

The true power of Dremio’s AI Semantic Layer is that it provides the "grounding" context for AI agents. Because the catalog contains rich metadata and defined relationships, the AI agent doesn't just see columns; it understands business concepts.

Data is no longer a static resource for human eyes; the Agentic Lakehouse is about building an ecosystem where AI can act on data as effectively as we do.

The Dremio Open Catalog is the vital bridge between open-source flexibility and enterprise-grade AI readiness. By moving from a "static mirror" of Iceberg files to a semantic, agent-ready architecture, Dremio allows organizations to finally realize the promise of a self-managing data lakehouse.

Dremio Catalog fundamentally changes the game for data lakehouse adoption. By providing a free, fully managed, and feature-rich service built on the open Apache Polaris project, Dremio removes the significant barriers to standing up a universal Iceberg catalog.

The true value of Dremio isn't just one feature, but its integrated, "all-in-one" platform. This approach contrasts sharply with the DIY method, which often results in a lakehouse that is perpetually a work-in-progress, stitched together with technical debt.

With a platform like the Dremio Agentic Lakehouse, you can leapfrog legacy architectures and move directly to a flexible, cost-effective, and AI-native data platform.

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 […]

Dremio's integrated platform transforms the agentic analytics challenge from a complex systems integration problem into a straightforward data conversation. By unifying federation, autonomous performance, a business-centric semantic layer, and conversational interfaces, Dremio eliminates the friction that has historically kept valuable insights locked away in data silos.

Success depends on three non-negotiable pillars: deep business context from a semantic layer, universal access through live data federation, and interactive speed delivered by autonomous performance features.