2026-08-04 • Alex Merced
Budgeting for Agentic Analytics When Every Question Costs Something Different
Budgeting for agentic analytics when every question costs something different: token economics, query economics, instrum...
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Data Lakehouses & Agentic Analytics
Authoritative guides to the modern data ecosystem — curated from Dremio's engineering blog.
Semantic Layer
The Semantic Layer: Definitive Guide
A comprehensive guide to the Semantic Layer — how it creates a single source of truth for metrics, powers headless BI, and makes AI agents answer business questions accurately.
Read on Dremio.com →Apache PolarisApache Polaris: The Catalog Standard for Lakehouses and AI
How Apache Polaris is emerging as the universal Iceberg catalog standard, enabling multi-engine interoperability and governed AI access across the lakehouse ecosystem.
Read on Dremio.com →Table FormatsWhat Are Table Formats and Why Were They Needed?
The origin story of open table formats — the problems with Hive, why Apache Iceberg, Delta Lake, and Hudi were created, and what they unlock for modern data platforms.
Read on Dremio.com →DremioWhat Is Dremio?
A clear-eyed breakdown of what Dremio is, how its semantic layer, query federation, Reflections, and Apache Arrow Flight power the Intelligent Lakehouse Platform.
Read on Dremio.com →Apache IcebergWhat Apache Iceberg Native Actually Means
Not all 'Iceberg support' is equal. This piece breaks down what it means to be genuinely Apache Iceberg native versus bolt-on, and why it matters for your lakehouse.
Read on Dremio.com →Open SourceOpen Source and the Data Lakehouse
How the Apache Software Foundation's open-source projects — Iceberg, Arrow, Parquet, Polaris — form the modular foundation of the modern open data lakehouse.
Read on Dremio.com →Agentic AIWhat Is Agentic Analytics?
Agentic AI is reshaping how organizations interact with data. This guide explains agentic analytics, the role of the semantic layer, and why query performance matters for AI agents.
Read on Dremio.com →Data LakehouseDefinitive Guide to the Data Lakehouse
The complete, authoritative guide to the Data Lakehouse architecture — what it is, why it supersedes the data warehouse + data lake combination, and how to build one.
Read on Dremio.com →AI & PerformanceHow Dremio Keeps Agentic Analytics Fast Without Manual Tuning
How Dremio's layered autonomous performance architecture — Reflections, caching, vectorized execution — handles unpredictable AI agent query patterns at interactive speed.
Read on Dremio.com →Recent Articles
Latest from IngestThis
Data Engineering, Data Architecture, and AI insights fresh from our writers.
2026-08-04 • Alex Merced
The Five Layers of an Agentic Lakehouse and Where the MCP Server Sits
The five layers of an agentic lakehouse and where the MCP server sits: storage, catalog, semantic layer, MCP gateway, an...
2026-08-04 • Alex Merced
Autonomous Table Optimization When Your Query Workload Stops Being Predictable
Autonomous table optimization when query workloads stop being predictable: observing file layout and query patterns, sco...
2026-08-04 • Alex Merced
Building Apache Iceberg Lakehouses That Run Without an Internet Connection
How to build an Apache Iceberg lakehouse that runs fully offline: storage, catalog, compute, cross-zone transfer, compli...
2026-08-04 • Alex Merced
Wiring Analytical Queries to Transactional APIs in Closed-Loop Decision Agents
Wiring analytical queries to transactional APIs in closed-loop decision agents: conditional writes, sagas with compensat...
2026-08-04 • Alex Merced
Surviving Optimistic Commit Collisions When Hundreds of Agents Write to Iceberg
Surviving optimistic commit collisions when hundreds of agents write to Iceberg: which conflicts are real, commit buffer...