Hitting the Iceberg REST Catalog Directly: Understanding the Differences Between Glue Data Catalog and S3 Tables
The article, published on DEV Community, explores the technical differences between using AWS Glue Data Catalog and S3 Tables as backends for the Apache Iceberg REST Catalog. The author demonstrates how to configure Apache Spark to connect directly to the Iceberg REST Catalog, bypassing the traditional Glue Data Catalog. Key points include that S3 Tables provide a native Iceberg catalog implementation with lower latency and reduced costs compared to Glue Data Catalog, which incurs additional charges for API calls. The article includes code examples for setting up Spark sessions with Iceberg REST Catalog endpoints and highlights that S3 Tables support transactional commits and snapshot management natively. The author notes that while Glue Data Catalog is widely used, S3 Tables offer a more optimized path for Iceberg workloads, especially for high-frequency catalog operations. The comparison covers performance benchmarks, showing that S3 Tables reduce catalog operation latency by up to 50% in some scenarios. The article concludes with recommendations for choosing between the two based on workload requirements, emphasizing that S3 Tables are better suited for real-time analytics and high-throughput environments.
Developers can reduce latency and costs by using S3 Tables as an Iceberg catalog instead of Glue Data Catalog.