Welcome!

This blog will contain articles about the Iceberg Data Lakehouse (using your data lake are your data warehouse with Apache Iceberg) and The Agentic Lakehouse (Lakehouses Optimized for working with AI Agents). What is Apache Iceberg? What is a Data Lakehouse? Where can I find more resources are all the types of content you'll find on this blog.

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

• Automating Table Maintenance Before Small Files Accumulate

  Published:May 24, 2026 |  at 10:00 AM

  Learn how Databricks Predictive Optimization, AWS S3 Tables, and Iceberg native actions automate compaction and snapshot management before small files degrade performance.

• Choosing the Right Iceberg Control Plane: Polaris vs. Unity Catalog vs. Cloud REST

  Published:May 24, 2026 |  at 10:00 AM

  Choosing an Apache Iceberg catalog? Compare open-source Apache Polaris, open Unity Catalog, and managed cloud REST control planes to unify your lakehouse.

• Clean Rooms for Privacy-Preserving Analytics

  Published:May 24, 2026 |  at 10:00 AM

  Data clean rooms enable secure multi-party analytics without sharing raw data. Learn how Databricks Clean Rooms, AWS Clean Rooms, and BigQuery differential privacy work.

• Building Composable Query Engines with Rust Runtimes

  Published:May 24, 2026 |  at 10:00 AM

  Apache DataFusion, Velox, and Substrait form the foundation of modern composable query engine stacks. Learn how these components fit together and when to use each.

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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