# Managed

> Browse 14 items tagged with Managed.

## Items

- [Upstash Vector](https://vectordb.ever.works/ko/items/upstash-vector) — 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.
- [Algolia](https://vectordb.ever.works/ko/items/algolia) — Search platform with vector search capabilities for fast and relevant AI-powered recommendations and discovery.
- [Amazon ElastiCache Vector Search](https://vectordb.ever.works/ko/items/aws-elasticache-vector-search) — Vector search extension for Amazon ElastiCache for Redis, featuring HNSW indexing for k-NN similarity, hybrid lexical+vector search with BM25 fusion capabilities. Used for enterprise semantic caching, real-time recommendations, and RAG applications. Integrated Redis module offers sub-microsecond latency vs standalone like Weaviate, optimized for hot data workloads.
- [Azure Cache for Redis Vector Search](https://vectordb.ever.works/ko/items/azure-cache-redis-vector) — Vector search plugin for Azure Cache for Redis via RediSearch module, supporting HNSW/Flat indexes, hybrid lexical+vector with BM25 fusion, metadata filtering. Suited for enterprise semantic caching, real-time RAG, and recommendations. Integrated caching layer provides sub-ms latency vs standalone vector DBs like Weaviate.
- [Cloudflare Vectorize](https://vectordb.ever.works/ko/items/cloudflare-vectorize) — Edge-native managed vector database integrated with Cloudflare Workers. Supports 50,000 namespaces and up to 5M vectors per index for low-latency applications.
- [DataStax Astra](https://vectordb.ever.works/ko/items/datastax-astra) — Managed database built on Cassandra with vector search capabilities, excelling in real-time updates and immediate consistency. Ideal for operational workloads requiring high throughput.
- [Google Vector Search](https://vectordb.ever.works/ko/items/google-vector-search) — Managed vector search service as part of Google Vertex AI, enabling efficient similarity search over high-dimensional vectors for AI applications.
- [Marqo](https://vectordb.ever.works/ko/items/marqo) — Managed vector database and search engine optimized for AI applications with multimodal search capabilities.
- [MongoDB Atlas Vector Search](https://vectordb.ever.works/ko/items/mongodb-atlas-vector-search) — Vector search capabilities integrated within the MongoDB ecosystem for general-purpose use cases. Suitable for light vector workloads combined with traditional database needs, offered as a managed service via MongoDB Atlas.
- [Rivestack](https://vectordb.ever.works/ko/items/rivestack) — Managed PostgreSQL with pgvector for AI workloads, featuring HNSW indexing and embedding search.
- [Turso](https://vectordb.ever.works/ko/items/turso) — Managed edge database using SQLite with sqlite-vec for per-tenant vector stores. Provides isolation via one database per tenant, suitable for edge deployments.
- [Vectara](https://vectordb.ever.works/ko/items/vectara) — Managed vector database platform for semantic search and retrieval augmented generation (RAG) in AI applications.
- [Vector.ai](https://vectordb.ever.works/ko/items/vectorai) — Vector.ai is a managed vector search platform that provides an API for creating, managing, and searching vector indices. It is designed to handle large volumes of high-dimensional data for efficient similarity search in machine learning and AI applications.
- [MongoDB Atlas Vector Search](https://vectordb.ever.works/ko/items/mongodb-atlas-vector) — Native vector search in MongoDB Atlas enabling semantic search alongside document data with HNSW indexing and filtering capabilities.

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