# Real Time Cache

> Browse 4 items tagged with Real Time Cache.

## Items

- [RedisVL](https://vectordb.ever.works/ar/items/redisvl) — RedisVL extends Redis with vector search via RediSearch module, HNSW indexes, hybrid BM25+vector. Great for caching/real-time RAG; vs dedicated VDBs leverages Redis speed/multi-model. Features: JSON payloads, streaming.
- [Redis Vector Search](https://vectordb.ever.works/ar/items/redis-vector-search) — Redis Vector Search (part of Redis Stack) enables vector similarity search on Redis with HNSW indexing, hybrid BM25+vector, and metadata filtering. It leverages Redis caching for low-latency real-time apps like semantic search. Vs dedicated DBs like Pinecone, Redis offers multi-model (JSON/KV + vectors) but requires more config for scale.
- [Azure Cache for Redis Vector Search](https://vectordb.ever.works/ar/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.
- [Redis LangCache](https://vectordb.ever.works/ar/items/redis-langcache) — Redis as vector database via RediSearch module supports HNSW/Flat indexes for real-time vector search in key-value store. Features: sub-ms latency, JSON payloads, modules ecosystem; use cases: caching + search hybrids. Vs dedicated VDBs, Redis excels in low-latency but limited scale for pure vectors.

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_Canonical page: https://vectordb.ever.works/ar/tags/real-time-cache_