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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.

An on-demand serverless configuration for OpenSearch Service that simplifies the operational complexities of managing OpenSearch domains, integrated with Knowledge Bases for Amazon Bedrock to support generative AI applications.

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.

Turbopuffer is a serverless, cloud-hosted vector database with managed paged storage, auto-scaling HNSW indexes, deterministic pay-per-use pricing, metadata filtering, and backups. Optimized for enterprise RAG and production AI apps with long-term, cost-efficient storage at scale. More economical operations than self-hosted Milvus or Zilliz Cloud for massive indexes.

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.

Managed serverless Postgres with pgvector for vector similarity search, featuring real-time subscriptions, Edge Functions, auto-HNSW indexing, serverless scaling, and RLS for multi-tenant isolation. Built for full-stack AI apps with auth, storage, and realtime. Postgres SQL + vectors outperforms dedicated DBs in integrated app development and cost for RAG/multi-tenant use cases.

Edge-native managed vector database integrated with Cloudflare Workers. Supports 50,000 namespaces and up to 5M vectors per index for low-latency applications.

Cloudflare's globally-distributed vector database running on their edge network. Provides low-latency vector search with automatic global replication and serverless pricing starting at $0.31/month.

Serverless data platform built on PostgreSQL with integrated vector search, full-text search engine, and ChatGPT capabilities, providing type-safe SDKs and database branching for modern applications.

Serverless object storage with native vector storage and query capabilities, supporting up to 2 billion vectors per index and 20 trillion per vector bucket. Optimized for production-scale AI workloads including RAG, semantic search, and conversational AI with sub-second query latencies. Integrates directly with Amazon Bedrock Knowledge Bases and Amazon OpenSearch Service.

SIGMOD 2024 paper introducing Vexless, a serverless vector data management system built on cloud functions that decouples compute and storage for elastic, pay-per-use vector similarity search.

A powerful RAG application platform delivering OpenAI-compatible serverless inference APIs for top open-source LLM models. Offers specialized batch processing for large-scale async AI workloads and document extraction capabilities designed for RAG applications, balancing cost-efficiency with high performance.

Serverless compute platform for AI with custom Rust-based infrastructure that spins up GPU-enabled containers in one second, supporting Python workloads with per-second billing.