Dremio Blog: Various Insights
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Dremio Blog: Various Insights
Semantic Layer Governance: Control What AI Agents Access
Semantic layer governance AI is the architectural pattern that closes this gap by enforcing data access controls structurally, at the layer every query must pass through, rather than procedurally, in workflows that agents simply skip. -
Dremio Blog: Various Insights
Building the Hybrid Lakehouse: Storage Platforms That Work With Dremio
In data analytics, it's the query engine that gets all the attention. It's where the SQL runs and where the performance story is told. But the storage layer underneath is just as important; it's the "lake" part of the "lakehouse" after all. Choose the wrong storage infrastructure and you're facing I/O bottlenecks no query engine […] -
Dremio Blog: Various Insights
Governing Your Lakehouse: Data Catalog Tools That Work With Dremio
A lakehouse without governance is a liability. Sure, you can query it, but can you trust it? Analysts find tables with no owner, no description, and no clear indication of whether what they're looking at is current. Likewise, compliance teams can't demonstrate data lineage and engineers can't assess the impact of a schema change before […] -
Dremio Blog: Various Insights
How Dremio Keeps Every BI Tool Consistent
Business intelligence tools are where data stops being infrastructure and starts being useful. Executives review performance in dashboards, product teams track metrics in reports, and finance runs variance analysis against actuals. In each case, the value only materialises if the connection between the tool and the underlying data is fast, reliable, and consistent. Dremio connects […] -
Dremio Blog: Various Insights
Life Sciences Analytics: Why Your Teams Keep Waiting on the Data Team
Life sciences analytics teams know the dynamic well: the question takes five minutes to ask and six weeks to answer. By the time the extract is ready, the interim analysis window has passed, the formulary negotiation is over, or the adverse event report is already pressing the 15-day FDA deadline. This is the default operating […] -
Dremio Blog: Various Insights
Dremio Earns 19 Top Rankings in BARC The Data Fabric Survey 26. Here Is What That Means for the Agentic Lakehouse.
The results are in. In BARC The Data Fabric Survey 26, one of the most rigorous independent evaluations of data platform software in the world, Dremio earned 19 top rankings and 4 leader positions in the Data Platforms peer group. In feedback collected from Dremio users, 100% said they would recommend Dremio, 100% rated their […] -
Dremio Blog: Various Insights
Manufacturing Analytics: Why Operational Leaders Are Done Waiting on IT
In SaaS data analytics, the gap between the question and the answer can determine whether a product decision gets made this week or next quarter. Your Customer Success team wants to know which accounts are drifting toward churn. Your RevOps lead wants to know where expansion signals are strongest. Your product team wants to understand […] -
Dremio Blog: Various Insights
Snowflake Competitors: More Affordable and Open Source Alternatives
Compare leading alternatives to Snowflake and learn how to choose the right data platform for performance, cost, and AI-ready analytics. -
Dremio Blog: Various Insights
4 Data Quality Tools to Keep Your Data In Shape
A lakehouse is only as useful as the data inside it. Query performance, governance, and semantic layers all depend on one assumption: that the underlying data is accurate, complete, and behaving as expected. When it isn't, dashboards return wrong answers, AI agents reason from bad inputs, and engineering teams spend days diagnosing problems that should […] -
Dremio Blog: Various InsightsDremio Named a Representative Vendor in the 2026 Gartner® Market Guide for Agentic Analytics. Here Is What We Think That Means for the Agentic Lakehouse.
We have news. The Gartner® Market Guide for Agentic Analytics, published February 9, 2026, maps the platforms shaping an emerging category: software that applies AI agents across the data-to-insight workflow. Among approximately 37 vendors listed, Dremio is recognized for its Agentic Lakehouse Platform as a Representative Vendor. We believe this reflects the data foundation we […] -
Dremio Blog: Various InsightsUsing Claude Code to Build an Iceberg Lakehouse
Using Claude Code to Build an Iceberg Lakehouse For years, building a production-grade data lakehouse required a specialized team: data engineers to design pipelines and to tune queries, and platform architects to manage table maintenance. Apache Iceberg changed the storage and table format equation, giving teams an open, vendor-neutral foundation for any scale of data. […] -
Dremio Blog: Various InsightsSub-Microsecond Timestamps: Dremio’s Iceberg v3 Precision Support
Most analytics workloads are fine with millisecond timestamps. A daily sales report doesn't care whether a transaction landed at 14:32:07.001 or 14:32:07.001423. But for the teams that do care about sub-millisecond precision, the lakehouse has historically been a weak link. Timestamps either got truncated on ingestion, stored as strings to preserve precision, or shoehorned into […] -
Dremio Blog: Various Insights
17 Best AI Integration Platforms for Agents and Automation
Explore leading AI and ML data integration services, learn selection criteria and see how Dremio powers agents and automation -
Dremio Blog: Various Insights
Top 11 Hadoop Alternatives to Use in 2026
Explore the 11 best alternatives to Hadoop in 2026, learn how to select the best solution for your enterprise to reduce costs and accelerate query performance. -
Dremio Blog: Various Insights
Enterprise Data Fabric: Architecture and Best Practices
Learn how enterprise data fabric supports AI, analytics and governed data access across modern hybrid and multi-cloud environments.
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