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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•Aug 2, 2026

  Apache Polaris 1.7.0 and the Quiet Work of Making a Catalog Trustworthy

  Apache Polaris 1.7.0 deep dive: idempotent writes, semantic models, stricter credential vending, orphan cleanup, and what the upgrade asks of you.

  Apache PolarisApache IcebergCatalog
• 31 MIN READ•Aug 2, 2026

  Designing Batch Pipelines That Write Well Into Apache Iceberg

  How to design batch pipelines that write well into Apache Iceberg: commit strategy, partitioning, sort order, write-audit-publish, and maintenance done right.

  Apache IcebergData EngineeringBatch Pipelines
• 31 MIN READ•Aug 2, 2026

  Apache Iceberg Support Across the Major Hyperscalers

  How AWS, Google Cloud, and Microsoft Azure actually support Apache Iceberg: storage, catalogs, maintenance, governance, and interoperability, layer by layer.

  Apache IcebergAWSGoogle Cloud
• 31 MIN READ•Jul 28, 2026

  Guardrails for Analytics Agents That Do More Than Answer Questions

  The risk isn't agents going rogue, it's agents acting correctly on bad input at machine speed. Here's how to classify actions by consequence, gate capability, and design approval steps people actually use.

  AI AgentsGuardrailsData Governance

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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