Does Increasing AWS Lambda Memory to 10GB Really Make It Faster? (AWS Lambda chDB/DuckDB PyIceberg Benchmark)

Original Japanese article : AWS Lambdaを10GBにすると本当に速くなるのか？（AWS Lambda×chDB/DuckDB×PyIceberg検証） Introduction I'm Aki, an AWS Community Builder ( @jitepengin ). In a previous article, I benchmarked Iceberg integration using AWS Lambda with DuckDB and chDB. Lightweight ETL with AWS Lambda, chDB, and PyIceberg (Compared with DuckDB) In that article, I tested two patterns on AWS Lambda: chDB × PyIceberg DuckDB × PyIceberg Memory sizes were set to 1024 MB, 2048 MB, and 3008 MB (the maximum without quota increase at the time). The results showed: For small datasets, increasing memory generally improved performance. For a large dataset (807 MB), 3008 MB was barely enough to complete processing. This time, I extended the experiment: What happens if we increase Lambda memory up to 10GB (10240 MB)? Increasing the Lambda Memory Quota To raise the Lambda memory limit beyond 3008 MB, you must request a quota increase. Important: You cannot increase Lambda memory from the Service Quotas console. Steps