A comprehensive directory of Apache Iceberg resources, including tutorials, guides, and educational materials for data engineers and developers.
Explores how combining data lakehouse, virtualization, and mesh architectures with Dremio solves modern data scaling and silo challenges.
A hands-on tutorial for building a Data Lakehouse on your laptop using Apache Iceberg, Spark, Nessie, Minio, and Dremio.
Explains why data professionals should adopt Dremio and Apache Iceberg for flexible, high-performance data lakehouse architecture.
Explores five key trends shaping the data lakehouse architecture, including storage evolution, table formats, and catalog competition.
Explains how Apache Iceberg uses delete files for efficient row-level data deletions without rewriting entire datasets.
Explains the role and structure of Apache Iceberg manifest files, key metadata components for tracking data files and optimizing queries in data lakehouses.
Explains the role and structure of the Apache Iceberg Manifest List file in managing table snapshots and optimizing data lakehouse queries.
Explains the critical role and structure of the metadata.json file in Apache Iceberg, the open-source table format for data lakehouses.
Explains the purpose and limitations of the Apache Iceberg REST Catalog specification for standardizing table operations.
Explains how Apache Iceberg brings ACID transaction guarantees to data lakes, enabling reliable data operations on open storage.
An introduction to data lakehouses, explaining what they are, why they're used, and how to migrate to this modern data architecture.
Explores Polaris, an open-source catalog service for managing Apache Iceberg tables in data lakehouses, covering its architecture, entities, and security.
Explains how Apache Iceberg's design ensures data reliability, atomic operations, and serializable isolation for large-scale data lakehouses.
A list of upcoming tech talks and events by Alex Merced, focusing on Apache Iceberg, data lakehouses, and data engineering topics.
A video course covering the fundamentals of lakehouse engineering using Apache Iceberg, Nessie, and Dremio for data management.
Explores Apache Iceberg's advanced partitioning features, including hidden partitioning and transformations, for optimizing query performance in data lakes.
Explains three key Apache Iceberg features for data engineers: hidden partitioning, partition evolution, and tool compatibility.
An introduction to Apache Iceberg, a table format for data lakehouses, explaining its architecture and providing learning resources.
Explores the evolution of Apache Iceberg catalogs, focusing on the current REST Catalog and future proposals for server-side optimizations.
