Autonomous table optimization when query workloads stop being predictable: observing file layout and query patterns, scoring compaction work, adaptive sort order, and cost discipline.
A field guide to the Apache Iceberg V4 proposals: adaptive metadata trees, single-file commits, typed statistics, column families, and what is safe to build on today.
An honest TCO framework for open lakehouses versus proprietary warehouses: five cost categories, measured numbers, sensitivity analysis, and where each side still wins.
How the Iceberg REST catalog became the lakehouse control plane: multi-table atomic commits, credential vending, capability negotiation, and what still breaks.
A dependency-first playbook for migrating legacy warehouses onto Apache Iceberg: snapshot vs migrate vs add_files, four-level parity validation, and federation-based cutover.
How AWS, Google Cloud, and Microsoft Azure actually support Apache Iceberg: storage, catalogs, maintenance, governance, and interoperability, layer by layer.
Walkthrough with the new trial of the Dremio Cloud Platform
A curated guide to mastering Apache Iceberg, data lakehouse architectures, and the emerging field of Agentic AI for data professionals.
Dive into the world of commercial Iceberg catalogs and discover how they enhance data lakehouse architectures for modern data engineering.
Exploring paths to a universal lakehouse catalog that supports multiple data formats and engines, building on Apache Iceberg's success.
Learn how to leverage Apache Iceberg with Apache Polaris and Apache Spark to build scalable and efficient data lakehouses.
What's Coming in Apache Iceberg v4: A Deep Dive into the Future of Open Table Formats
Understanding Iceberg, Delta Lake, Hudi, Paimon, and DuckLake
What is the Data Lakehouse and the Data Lakehouse Ecosystem? This comprehensive guide covers everything you need to know about the Data Lakehouse architecture, open table formats like Apache Iceberg, Delta Lake, Apache Hudi, and Apache Paimon, and the modern data ecosystem that supports them.
Unlocking the Power of Agentic AI with Apache Iceberg and Dremio
Learn how Apache Iceberg tables can degrade over time without optimization and what issues this causes for performance, cost, and governance.
Guide on How to Be Part of the Lakehouse Community
Introductory Course to Data Engineering for Apache Iceberg Lakehouses
Benefits of Apache Iceberg Partition Evolution and Hidden Partitioning
Benefits of Apache Iceberg
How to run SQL on your Excel files easily
Learning about Apache Iceberg
Java, Rest and the expanding open lakehouse ecosystem
Ingesting Data and Building BI Dashboards
Apache Iceberg, Apache Arrow, Nessie, Ibis, Substrait
Understanding how catalogs work and which one to choose
Disrupting the Snowflake/Databricks status quo
Understanding how catalogs work and which one to choose
Understanding how catalogs work and which one to choose
Learning the Standard SQL Syntax
Understanding the Value of the Data Lakehouse
Deep Dive in Data Lake Table Partitioning
Understanding the Data Vault Style of Data Warehouse Modeling
Understanding how to choose a table format
The Future of Data Platforms
Resources for learning how to Engineer an Open Data Lakehouse
Nessie is the only open-source catalog implementation specifically for Apache Iceberg.
This is where the combined power of Dremio’s Lakehouse Management features and Project Nessie's catalog-level versioning comes into play.
Why is Dremio so useful for Apache Iceberg data lakehouses