Alex Merced's Data, Dev and AI Blog

Topic

Apache Polaris

18 posts tagged “Apache Polaris”.

  1. 20 min read

    The Five Layers of an Agentic Lakehouse and Where the MCP Server Sits

    Someone on your team connects an AI desktop client to a query engine, asks a question about last quarter, and gets an answer in fifteen seconds. It…

  2. 20 min read

    Why Agentic AI Needs a Governed Semantic Layer Behind the Model Context Protocol

    An executive asks an AI assistant what revenue looked like last quarter. The assistant writes SQL against the warehouse, sums an amount column, and…

  3. 20 min read

    Cross-Cloud Credential Vending in Apache Polaris and the End of Permanent Storage Keys

    Pull up the configuration for any Spark cluster that reads a data lake and look for the storage credentials. In most organizations you find an IAM…

  4. 20 min read

    How the Iceberg REST Catalog Turned Into the Lakehouse Control Plane

    A dbt run updates a fact table and two dimension tables. The fact table commit succeeds. The second dimension commit fails on a conflict. For the…

  5. 31 min read

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

    A Spark job commits a table update. The catalog writes the change to Postgres. Then the network drops between the catalog and the client, and the…

  6. 30 min read

    Wiring an AI Agent to Apache Polaris with the Model Context Protocol

    An engineer opens Cursor, types "what tables do we have in the sales namespace, and which ones have a customerid column," and gets an answer in four…

  7. 31 min read

    Governing Iceberg Tables Across Regions Without Three Sets of Permissions

    An engineer needs to join sales data in eu-west-1 with product data in us-east-1. The sales tables live in a Polaris instance the European team runs.…

  8. 31 min read

    The Breakdown of the Open Lakehouse in 2026: Iceberg, Arrow, Polaris, Parquet, and Ossie, and How to Actually Build One

    If you have followed the data world for the past few years, you have heard the phrase "open lakehouse" often enough that it may have started to sound…

  9. 17 min read

    Apache Polaris and Multi-Engine Iceberg Catalogs

    Apache Iceberg solved a hard problem: it gave analytics teams a table format that multiple engines can read and write without corrupting each other's…

  10. 29 min read

    The State of Apache Polaris in July 2026: From Incubating Catalog to the Governance Layer of the Open Lakehouse

    I have a personal stake in this one, so let me declare it up front. Apache Polaris was co-created by Snowflake and Dremio, I work at Dremio, and I…

  11. 15 min read

    Multi-Engine Catalog Federation with Apache Polaris: Syncing Google Cloud, AWS, and Azure Metadata

    Open table formats changed the data lakehouse conversation, but they did not finish it. A table can be stored in an open format and still be hard to…

  12. 15 min read

    Unity AI Gateway vs Apache Polaris Control Planes

    The right comparison is not vendor scoreboard. It is closed AI governance gateway versus open catalog control plane. For enterprise architects…

  13. 7 min read

    2025 Year in Review Apache Iceberg, Polaris, Parquet, and Arrow

    A look back at key developments in Apache Iceberg, Polaris, Parquet, and Arrow in 2025.

  14. 19 min read

    Comprehensive Hands-on Walk Through of Dremio Cloud Next Gen (Hands-on with Free Trial)

    Walkthrough with the new trial of the Dremio Cloud Platform

  15. 8 min read

    2025-2026 Guide to Learning about Apache Iceberg, Data Lakehouse & Agentic AI

    A curated guide to mastering Apache Iceberg, data lakehouse architectures, and the emerging field of Agentic AI for data professionals.

  16. 19 min read

    An Exploration of the Commercial Iceberg Catalog Ecosystem

    Dive into the world of commercial Iceberg catalogs and discover how they enhance data lakehouse architectures for modern data engineering.

  17. 13 min read

    Building a Universal Lakehouse Catalog - Beyond Iceberg Tables

    Exploring paths to a universal lakehouse catalog that supports multiple data formats and engines, building on Apache Iceberg's success.

  18. 25 min read

    Intro to Apache Iceberg with Apache Polaris and Apache Spark

    Learn how to leverage Apache Iceberg with Apache Polaris and Apache Spark to build scalable and efficient data lakehouses.

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