The Dremio Blog

Most data teams think about lineage at the table or column level. Which pipeline wrote to this table? Which upstream source feeds this column? Those are useful questions, but they stop short of what actually matters in an audit or incident investigation: which specific rows were affected, by which operation, and when. Apache Iceberg v3 […]

Dremio offers three distinct integration points to the data in your lakehouse. This gives users the freedom to pick the interface, models, and tools that are right for them. Whether you're a business user, a seasoned data analyst, or a developer, we have an integration that will suit how you like to work. The built-in […]

Agentic AI is how leading financial institutions turn risk aggregation and regulatory reporting from a slow, manual burden into a real‑time, always on advantage, boosting accuracy, slashing costs, and accelerating insight. Dremio’s Agentic Lakehouse gives financial institutions the data foundation and AI agents they need to industrialize risk aggregation and regulatory reporting, with higher accuracy, […]

Working with JSON in an Iceberg lakehouse has always been a compromise: you either store JSON as VARCHAR strings and accept the performance hit every time a query needs to extract a field, or you flatten the JSON into a wide table of nullable columns and watch your schema bloat. Both work fine but have […]

Financial crime has become a trillion‑dollar problem, and the only sustainable way to fight it is with AI‑driven, real‑time analytics on complete, well‑governed data. Dremio’s Agentic Lakehouse platform is designed to give Financial Services organizations exactly what effective fraud and AML programs need: unified data, governed access, and sub‑second analytics across historical and streaming data. […]

The third annual Iceberg Summit is happening this week and it’s rapidly growing into one of the must attend data events for the year. Why? Well, Iceberg won the table format wars a couple years ago because companies wanted to avoid lock-in and they wanted interoperability. The Iceberg lakehouse also quietly became the default data […]

For years, the promise of the open lakehouse was simple: store your data once, query it with any tool, and never get locked into a single vendor's ecosystem. Apache Iceberg made that promise real. It became the industry-standard table format because it worked, it was open, and it kept getting better. Iceberg version 3 (V3) […]

If you haven’t arrived at this conclusion, you will. If you’ve started transitioning some of your analytics to agents, you’ll know you’ll be here soon. Reporting is fundamentally different, and 100x better in the AI-era. I don’t say that to be provocative. I say it because of what we’ve changed internally at Dremio over the […]

Personality typing is a time-honoured tradition in tech. You've taken the Myers-Briggs, argued about whether you're really an INTJ, and been sorted into a primary-coloured group that allegedly encapsulates your work persona. But the test nobody was brave enough to publish is the one that actually matters to your daily work: which Dremio feature matches […]

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 […]