The New S3 Features Most Engineers Missed

Amazon S3 Tables and S3 Vector Buckets are the two biggest changes to S3 in years, and most engineers are still storing data the old way. S3 has been around since 2006, but the last two years added two features that change how data lakes and embeddings get stored. S3 Tables give you Apache Iceberg storage that is fully serverless, with compaction and metadata handled by AWS instead of you. S3 Vector Buckets store embeddings for RAG and AI agents without a separate vector database to run. Both plug straight into the query and AI tools you already use. 📚 What you'll learn: 1️⃣ Why Hive tables broke down and how Apache Iceberg fixes it 2️⃣ How S3 Tables store data in Iceberg format with zero maintenance 3️⃣ Creating an S3 Table bucket and namespace in under 5 minutes 4️⃣ How S3 Vector Buckets stand in for a managed vector database on RAG 🚨 Start Your AWS Journey with KodeKloud: https://kode.wiki/4riGWhL ☁️ AWS & Cloud Playlist: https://www.youtube.com/playlist?list=PL2We04F3Y_41Q_1_7cuOa9HDcFziJPWpt ⏰ Timestamps: 00:00 - Introduction 01:04 - What S3 buckets have always been used for 02:32 - Amazon S3 Tables: serverless Iceberg storage 04:58 - Demo: Creating S3 Tables 07:24 - S3 Vector Buckets 09:25 - Demo: Create a Vector Bucket and Vector Index 11:27 - Conclusion - Which S3 data should you migrate? 🔔 Subscribe for more AWS, data engineering, and AI engineering on KodeKloud #AmazonS3 #S3Tables #S3VectorBuckets #AWS #ApacheIceberg #S3Iceberg #DataEngineering #VectorDatabase #RAG #DataLake #AWSTutorial #CloudComputing #Embeddings #Serverless #KodeKloud