Category: Amazon S3 Tables

Managing large-scale data analytics across diverse data sources has long been a challenge for enterprises. Data teams often struggle with complex data lake configurations, performance bottlenecks, and the need to maintain consistent data governance while enabling broad access to analytics capabilities. Today, Starburst announces a powerful solution to these challenges by extending their Apache Iceberg […]

UPDATE (7/31/2025): Firehose can directly access S3 Tables in Glue Data Catalog without requiring resource links. Businesses are increasingly adopting real-time data processing to stay ahead of user expectations and market changes. Industries such as retail, finance, manufacturing, and smart cities are using streaming data for everything from optimizing supply chains to detecting fraud and […]

Modern data lakes integrate with multiple engines to meet a wide range of analytics needs, from SQL querying to stream processing. A key enabler of this approach is the adoption of Apache Iceberg as the open table format for building transactional data lakes. However, as the Iceberg ecosystem expands, the growing variety of engines and languages has […]

UPDATE (12/19/2024): Added guidance for Amazon EMR setup. Customers commonly use Apache Iceberg today to manage ever-growing volumes of data. Apache Iceberg’s relational database transaction capabilities (ACID transactions) help customers deal with frequent updates, deletions, and the need for transactional consistency across datasets. However, getting the most out of Apache Iceberg tables and running it […]

Today businesses managing petabytes of data must optimize storage and processing to drive timely insights while being cost-effective. Customers often choose Apache Parquet for improved storage and query performance. Additionally, customers use Apache Iceberg to organize Parquet datasets to take advantage of its database-like features such as schema evolution, time travel, and ACID transactions. Customers […]