The Dremio Blog

Ask a typical data engineering team what percentage of their company's data they can actually query. The honest answer will be low, probably around 20%. The rest sits in object storage as PDFs, email threads, customer feedback forms, call transcripts, maintenance logs, and scanned documents. It's all there. It's all stored. And for the purposes […]

The data warehouse was never a product. It was an architectural intent. Here is why the lakehouse is its rightful successor, built on open standards.

Most companies process terabytes of JSON daily, yet querying it often requires brittle pre-processing pipelines and rigid data contracts. This has analysts and data engineers wasting hours defining explicit schemas just to run a simple aggregation. Dremio eliminates this friction by allowing you to query JSON directly in the lakehouse with complete schema-on-read flexibility. Without […]

Every enterprise has a data problem hiding in plain sight. Not the kind that shows up in board decks about cloud migration or AI strategy. The quieter kind: petabytes of files sitting in NetApp ONTAP systems — financial records, engineering documents, customer data, sensor logs — that power daily operations but stay invisible to every […]

Agentic AI is Front and Center for Financial Services Strategy Agentic AI is now at the center of competitive strategy in financial services, moving from pilots to production at scale. In this landscape, Dremio’s lakehouse-first approach gives banks, insurers, and wealth managers the data foundation they need to operationalize AI quickly and safely. AI Trends […]

For decades, the traditional data experience has been defined by friction, with business teams frequently required to wait. Waiting for SQL experts to draft queries, waiting for ETL pipelines to refresh, and waiting for static dashboards to render. This reactive model has gone past being just a bottleneck and now represents an existential risk for […]

The Apache Iceberg community recently finalised a new File Format API, scheduled for the upcoming 1.11.0 release. It is a strategic architectural shift that decouples the object model from the physical storage layout. The aim? To make file formats engine-agnostic, so Apache Iceberg can integrate with new formats without rewriting the core engine logic every […]

How data architects can close the gap between the AI mandate and the infrastructure that actually delivers it If you are a data architect right now, you are likely operating under some version of the same executive mandate: implement AI, and do it fast. The pressure is real. So is the gap between what leadership […]

Today we're making it super simple to use Claude, Claude Cowork, and Claude Code with Dremio.  The new Claude connector for Dremio Cloud lets anyone instantly connect Anthropic's Claude to their lakehouse.  

The Data Crisis Crippling Financial Services Most financial institutions today face the same bottleneck: fragmented, slow, and costly data systems that cripple the adoption of AI. Analysts wait hours for risk reports. Data engineers spend most of their time tuning queries instead of innovating. And autonomous AI agents hit performance walls and data inconsistencies that […]

Across Europe, organizations are modernizing analytics and AI while tightening requirements around data control, jurisdiction, and operational accountability. What customers are increasingly seeking is straightforward: the flexibility of open architectures, the speed needed for modern workloads, and the confidence that their service operations, support, and contracting align with European expectations. Today, I’m excited to share […]

Most enterprise AI projects fail at the same place. Not the model. Not the infrastructure. The data. Specifically: the AI doesn't understand the data well enough to act on it accurately, and it can't reach most of the data anyway. These two problems compound each other. A model that can only see 30% of your […]

Data engineering teams are often defined by the gap between a business question and a verified answer. Requests languish in backlogs while engineering teams struggle with ETL pipelines and the technical debt of siloed warehouses. When reports finally arrive, the data is frequently stale, leading to debating the accuracy of the numbers rather than the […]

The data lakehouse market has moved past the “is this real?” phase. According to Forrester’s The Data Lakehouses Landscape, Q1 2026, lakehouses are now the default architectural choice for modern analytics and AI workloads, driven by the need to simplify data architectures, control costs, and support modern analytics and AI workloads. For technology leaders navigating […]

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