A technical guide on using Flink SQL to write data to Apache Iceberg tables stored on AWS S3, with metadata managed by the AWS Glue Data Catalog.
A monthly roundup of curated links and articles covering data engineering, Kafka, stream processing, and AI, with top picks highlighted.
An introductory guide to data engineering, explaining its role, key concepts, and how it differs from data science in the modern data ecosystem.
Explains batch processing fundamentals for data engineering, covering concepts, tools, and its ongoing relevance in data workflows.
An introduction to data warehousing concepts, covering architecture, components, and performance optimization for analytical workloads.
Explains data lakes, their key characteristics, and how they differ from data warehouses in modern data architecture.
Explores the importance of data quality and validation in data engineering, covering key dimensions and tools for reliable pipelines.
Explains core data engineering concepts: metadata, data lineage, and governance, and their importance for scalable, compliant data systems.
Explains the importance of data storage formats and compression for performance and cost in large-scale data engineering systems.
Explores core principles of scalable data engineering, including parallelism, minimizing data movement, and designing adaptable pipelines for growing data volumes.
Explains the data lakehouse architecture, a unified approach combining data lake scalability with warehouse management features like ACID transactions.
Explores Apache Iceberg, Arrow, and Polaris—three key technologies powering modern, high-performance data lakehouse platforms.
Explains the Model Context Protocol (MCP), an open standard for connecting AI agents and LLMs to external data sources and tools, enabling interoperability.
A comprehensive 2025 guide to Apache Iceberg, covering its architecture, ecosystem, and practical use for data lakehouse management.
A technical guide on designing and implementing a modern data lakehouse architecture using the Apache Iceberg table format in 2025.
A look at 10 upcoming features and enhancements for the Apache Iceberg data lakehouse table format, expected in 2025.
A guide to setting up and using Dremio's Auto-Ingest feature for automated, event-driven data loading into Apache Iceberg tables from cloud storage.
A tutorial on using SQL with Apache Iceberg tables in the Dremio data lakehouse platform, covering setup and core operations.
Explores how Dremio and Apache Iceberg create AI-ready data by ensuring accessibility, scalability, and governance for machine learning workloads.
A hands-on tutorial for setting up a local data lakehouse with Apache Iceberg, Dremio, and Nessie using Docker in under 10 minutes.
