Turbopuffer

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.

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.

Upstash Vector is a serverless, cloud-hosted vector database with managed scale-to-zero autoscaling, pay-per-use pricing, low-latency search, and support for billions of vectors across regions. Ideal for enterprise RAG and production AI similarity search applications. Simpler and more cost-effective than self-hosted Milvus or Zilliz for variable workloads.

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.

Pinecone is a managed, serverless vector database optimized for low-latency semantic search and recommendations. Auto-scales, supports pod/serverless pods, hybrid sparse-dense. Best for production RAG without ops overhead; vs Weaviate more focused on pure vectors. Features: metadata filtering, real-time updates.