Amazon S3 Vectors

Amazon Aurora Serverless v2 is a cloud-hosted, serverless relational database (Postgres/MySQL compatible) with pgvector support for managed vector workloads, featuring auto-scaling compute/memory, pay-per-use pricing, automated backups, and multi-AZ/multi-region high availability. Suited for enterprise RAG via Amazon Bedrock Knowledge Bases and production AI apps. Provides easier operations than self-hosted Milvus or Postgres, deeply integrated with AWS unlike standalone Zilliz.

Amazon Aurora Machine Learning provides managed vector storage and search capabilities integrated into Aurora PostgreSQL for AI workloads on AWS. Key features include serverless scaling, direct ML model calls via SQL for embeddings, and seamless integrations with Bedrock and SageMaker. Perfect for RAG pipelines and enterprise AI applications, it simplifies vectorization and abstracts infrastructure compared to self-hosted options like Milvus.

AstraDB is a serverless, cloud-hosted vector database built on Cassandra, offering fully managed infrastructure with auto-scaling, auto-sharding, pay-per-use pricing, automated backups, and multi-region/multi-cloud deployments. Ideal for enterprise RAG pipelines, production AI applications, and hybrid vector-wide-column workloads. Provides easier operations than self-hosted Milvus, with greater durability compared to Zilliz.

Momento Vector Index is a serverless, cloud-hosted vector database with managed auto-scaling infrastructure, pay-per-use pricing, real-time backups, and low-latency retrieval for billions of vectors. Suited for enterprise RAG, production AI apps like semantic search and recommendations. Offers simpler operations than self-hosted Milvus, with more transparent pricing than Zilliz or Pinecone.

Serverless Postgres with native pgvector support for vector embeddings and similarity search. Features instant provisioning, autoscaling, and scale-to-zero with separated compute and storage. This is a commercial managed service with free tier.

Managed serverless Qdrant with pay-per-query, auto-scale for vector similarity search. Supports filtering, Python/JS/Go/Rust SDKs (gRPC/REST/HTTP). Enterprise RAG/recommendations; easier scaling than self-hosted Qdrant.