Product Insights from the Dremio Blog
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Product Insights from the Dremio Blog
Announcing Arrow Database Connectivity (ADBC) in Microsoft Power BI’s Connector for Dremio
We’re excited to share, in partnership with Microsoft, that Dremio is the first agentic lakehouse platform to fully support the open source Apache Arrow Database Connectivity (ADBC) driver for Power BI, bringing next-generation performance to your analytics. Whether you’re working with Dremio Cloud or Dremio Software, this enhancement is available across Power BI Desktop, Power […] -
Dremio Blog: Open Data Insights
Ingesting Data into Apache Iceberg Using Python Tools with Dremio Catalog
In this blog you will learn how to connect each tool to a REST catalog like Dremio Catalog, using bearer tokens and vended credentials to keep your pipelines secure and portable. -
Product Insights from the Dremio Blog
Hands-on Introduction to Dremio Cloud Next Gen (Self-Guided Workshop)
Dremio Next Gen Cloud represents a major leap forward in making the data lakehouse experience seamless, powerful, and accessible. Whether you're just beginning your lakehouse journey or modernizing a complex data environment, Dremio gives you the tools to work faster and smarter—with native Apache Iceberg support, AI-powered features, and a fully integrated catalog. From federated queries across diverse sources to autonomous performance tuning, Dremio abstracts away the operational headaches so you can focus on delivering insights. And with built-in AI capabilities, you're not just managing data—you’re unlocking its full potential. -
Product Insights from the Dremio Blog
Introducing Dremio Cloud, The Agentic Lakehouse
We’re excited to announce Dremio Cloud, The Agentic Lakehouse—the lakehouse built for agents and managed by agents. This milestone marks a major leap forward in Dremio’s evolution, reimagining the modern lakehouse for the agentic era, where intelligent systems collaborate with humans to deliver insights, automate operations, and continuously optimize performance. As organizations accelerate their AI […] -
Product Insights from the Dremio Blog
Introducing the VS Code Extension for Dremio
Many data engineers and data analysts spend much of their day in Visual Studio (VS) Code, writing SQL, testing queries, and working with data. Constantly switching between tools disrupts productivity and the user work flow. The VS Code extension for Dremio brings the power of the agentic lakehouse directly into your development environment, enabling you […] -
Product Insights from the Dremio Blog
Dremio’s Lakehouse AI Agent: From Questions to Actions
Organizations cannot implement AI quickly when data is fragmented across systems, ungoverned, and lacks the business context AI needs to deliver accurate results. Teams juggle schema knowledge, joins, query tuning, visualization tools, and governance checks before they can answer even a simple business question. With Dremio's Agentic Lakehouse—the only data platform built for agents and […] -
Product Insights from the Dremio Blog
AI Functions Power Faster Agentic Analytics and Insights
The rapid growth of the use of AI throughout the modern data stack has transformed how organizations extract insights from their data. With our latest release, we're excited to announce the general availability of AI Functions — a capability that brings the power of Large Language Models (LLMs) directly into SQL execution, making Dremio’s Agentic […] -
Product Insights from the Dremio Blog
Get Enhanced MCP Server Data Exploration with Dremio’s Agentic Lakehouse
Discover how Dremio’s Next Generation Cloud and enterprise MCP Server simplify data exploration with AI-driven queries, governance, and natural-language SQL. -
Product Insights from the Dremio Blog
Apache Iceberg Table Performance Management with Dremio’s OPTIMIZE
Performance management for Apache Iceberg tables isn’t just about cleaning up small files, it’s about ensuring your data layout evolves in step with your ingestion patterns and query workloads. Dremio’s OPTIMIZE command provides the precision engineers need: merging, splitting, and reclustering data into efficient layouts while keeping metadata lean. With its flexible parameters, you can tailor compaction jobs to strike the right balance between optimization depth, runtime, and cost. At the same time, Dremio’s auto-optimization features mean you don’t always have to run these jobs manually. By letting Dremio continuously monitor and optimize Iceberg tables in the background, your most critical datasets stay query-ready without the overhead of constant maintenance. -
Product Insights from the Dremio Blog
Minimizing Iceberg Table Management with Smart Writing
The real secret to minimizing Iceberg table maintenance isn’t running more optimization jobs, it’s writing smarter data from the very beginning. By combining batch and streaming ingestion best practices, designing thoughtful partitioning and clustering strategies, tuning table properties, and monitoring file health, you can dramatically reduce the frequency and cost of downstream operations like OPTIMIZE. -
Product Insights from the Dremio Blog
Apache Iceberg Table Storage Management with Dremio’s VACUUM TABLE
Apache Iceberg’s snapshot model is a game-changer for time travel, auditing, and recovery, but it comes with a responsibility: old data must be managed carefully. Without proactive cleanup, tables can accumulate unnecessary files, driving up storage costs, slowing queries, and even creating compliance risks. Dremio’s VACUUM TABLE command provides the control data engineers and architects need to: Expire outdated snapshots, keeping only the versions that align with retention policies. Permanently remove deleted data to meet GDPR and CCPA requirements. Clean up orphan files to ensure storage remains lean and predictable. -
Product Insights from the Dremio Blog
Using Dremio’s MCP Server with Agentic AI Frameworks
This is exactly where MCP and A2A come together. MCP ensures that agents can securely interact with enterprise tools like Dremio, accessing trusted data through well-defined interfaces. A2A, in turn, provides the framework for those agents to collaborate, delegating tasks, exchanging results, and orchestrating end-to-end workflows. -
Product Insights from the Dremio Blog
Data Regulations in Food & Agriculture Supply Chains and Dremio’s Lakehouse Solution
Regulatory change in the food and agriculture supply chain is no longer about periodic paperwork, it’s about maintaining continuous, trustworthy, and accessible data. Whether it’s proving product lineage within 24 hours for the FDA, reporting Scope 3 emissions under the EU’s CSRD, or ensuring supplier compliance through due diligence laws, the common denominator is data complexity. -
Product Insights from the Dremio Blog
Why Dremio is the Ideal Secure Data Platform for Transportation & Automotive Companies
The transportation and automotive industry sits at a unique inflection point: vehicles are now data platforms as much as they are machines. With each car, truck, or bus generating gigabytes of telemetry, location, and sensor data every hour, the potential for innovation is enormous. Yet the regulatory landscape, from U.S. privacy laws to EU mandates on data portability and global cybersecurity standards, makes it clear that this data must be handled with care. Non-compliance isn’t just a legal risk; it undermines consumer trust and can derail new business models before they gain traction. -
Product Insights from the Dremio Blog
Why Dremio is an Ideal Data Platform for Telecom Companies: Navigating Data Regulations and Security
Telecom companies cannot afford to rely on platforms that “might” meet regulatory standards , they need proven, auditable compliance. Dremio is designed with security and certification at its core, giving providers confidence that their data practices align with industry and legal obligations.
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