https://kane.mx/tags/s3-vectors/Recent content in S3 Vectors on The roadHugo -- gohugo.ioenWed, 27 May 2026 00:00:00 +0000https://kane.mx/posts/2026/s3-vectors-vs-opensearch/Wed, 27 May 2026 00:00:00 +0000https://kane.mx/posts/2026/s3-vectors-vs-opensearch/ <p>Choosing a vector store on AWS for generative AI (GenAI) workloads used to be a one-line decision: pick Amazon OpenSearch Service or its serverless variant (AOSS) and move on. That changed when <a href="https://docs.aws.amazon.com/AmazonS3/latest/userguide/s3-vectors.html">Amazon S3 Vectors</a> went GA in 2025. By storing vector data directly in S3 and pricing it on a fully consumption-based model, S3 Vectors has reset the cost-performance frontier for vector search.</p> <p>This post is not a rehash of the official documentation. It distills selection and tuning experience across more than 30 production GenAI projects shipped over the past year. You will get a decision tree, the cost-crossover math between the two services, and the specific migration pitfalls that bite hardest in practice — including the cosine-distance range mismatch and the metadata structure constraints.</p> <p><a href="https://kane.mx/posts/2026/s3-vectors-vs-opensearch/">Read More</a></p>