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Iceberg Lakehouse is the technical encyclopedia for Apache Iceberg, lakehouse catalogs, the Agentic Lakehouse, and modern data architecture. Whether you are learning what table formats are, how to deploy Apache Polaris, or how to connect engines to Iceberg tables, you will find the definitive reference material here.

This blog is not affiliated with the Apache Foundation or the Apache Iceberg project whose official page is iceberg.apache.org.

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Recent Posts

• 31 MIN READ•Jul 25, 2026

  Governing What Agents Cost You

  Agents break the four assumptions analytics platforms were built on. A practical guide to identity, budgets, semantic layers, caching, and instrumentation for agent workloads.

  AI agentscost governancedata platform
• 31 MIN READ•Jul 25, 2026

  Every AI Model Family That Matters in Mid-2026

  A full survey of the AI model landscape in mid-2026: frontier families, open-weight labs, local inference, specialists, and how to build a routing layer instead of a dependency.

  AI modelsLLMopen weights
• 31 MIN READ•Jul 25, 2026

  Freshness Is a Contract, Not a Note on a Dashboard

  Data freshness needs to become an engineering contract with a measurable value, an owner, and consequences. How to decompose lag, make freshness queryable, and keep agents honest.

  data freshnessdata qualityapache iceberg
• 31 MIN READ•Jul 25, 2026

  The Apache Iceberg Market in the Middle of 2026

  A survey of the Apache Iceberg market in July 2026: the state of the specification, platform support, the acquisition wave, the catalog contest, and how to evaluate real Iceberg support.

  apache iceberglakehousedata engineering

Must Reads on Iceberg, Agentic AI and Lakehouse from Around the Web

• The Definitive Guide to the Semantic Layer

  Understand what a semantic layer is, why it matters for modern data architectures, and how it creates a consistent, governed layer between raw data and business consumers.

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• Apache Polaris: The Catalog Standard for Lakehouses and AI

  A deep dive into Apache Polaris, the open-source catalog that is emerging as the standard for managing Iceberg tables across multi-engine Lakehouses and AI workloads.

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• What Are Table Formats and Why Were They Needed?

  Explore the history and motivations behind open table formats like Apache Iceberg, Delta Lake, and Apache Hudi, and why they solved critical problems in big data engineering.

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• What is Dremio?

  A comprehensive overview of Dremio's Lakehouse platform — how it unifies data access, accelerates queries, and powers self-service analytics across cloud and on-premise sources.

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• What Apache Iceberg Native Actually Means

  Not all Iceberg integrations are equal. This article breaks down what it truly means for a platform to be 'Apache Iceberg native' and why the distinction matters for your architecture.

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• Open Source and the Data Lakehouse

  A survey of the open source ecosystem powering modern Data Lakehouses — from Apache Iceberg and Nessie to Apache Arrow and Spark — and how they work together.

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• What is Agentic Analytics?

  Discover how AI agents are transforming analytics pipelines — autonomously querying data, generating insights, and taking actions — and what it means for the future of the Lakehouse.

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