# Vector Database 2026

> Browse 8 items tagged with Vector Database 2026.

## Items

- [Elasticsearch Vector Search](https://vectordb.ever.works/items/elasticsearch-vector-search) — Lucene KNN vector plugin for Elasticsearch search engine, enabling hybrid lexical+vector search, BM25 fusion, HNSW/IVF indexes for ANN. Used for enterprise search, RAG, multimodal apps. Integrated vs standalone like Weaviate: superior hybrid text handling but higher resource footprint.
- [OpenSearch Vector Search](https://vectordb.ever.works/items/opensearch-vector-search) — k-NN vector plugin for OpenSearch (Lucene-based), supporting hybrid lexical+vector, BM25 fusion, HNSW/IVF indexes, multimodal. For enterprise RAG, semantic search. Integrated vs standalone like Weaviate: excels in hybrid text+vector but heavier footprint.
- [AlayaDB](https://vectordb.ever.works/items/alayadb) — Hybrid database-inference engine that converts documents to tensors via LLM forward pass, storing in a KV cache for optimized retrieval. Features integrated storage and inference with advanced indexing for fast context retrieval in RAG pipelines. Suited for LLM applications and semantic search; differs from Milvus by embedding inference, more specialized than Qdrant's pure vector storage.
- [Manu — A Cloud Native Vector Database Management System](https://vectordb.ever.works/items/manu-a-cloud-native-vector-database-management-system) — VLDB 2022 paper introducing Manu, a cloud-native vector database management system designed for scalable similarity search in cloud environments with separated storage and compute architecture.
- [PostgreSQL (with pgvector)](https://vectordb.ever.works/items/postgresql-with-pgvector) — Powerful open-source object-relational database system that, with the pgvector extension, serves as a capable vector database for AI applications. Widely used from small projects to large-scale enterprise systems, and offered as managed services by major cloud providers.
- [VAST AI OS](https://vectordb.ever.works/items/vast-ai-os) — GPU-accelerated platform from VAST Data that includes a native vector database, designed for enterprise AI workloads including multi-agent systems, video-reasoning, and high-volume RAG. It combines vector embeddings with structured data and metadata in unified tables, enabling hybrid queries across modalities without orchestration layers or external indexes.
- [VAST CNode-X](https://vectordb.ever.works/items/vast-cnode-x) — GPU-accelerated server from VAST Data that combines the VAST AI OS with NVIDIA data-processing libraries and onboard NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. Designed for enterprise AI workloads requiring high-throughput vector search, data vectorization, and inference, it leverages the NVIDIA AI Data Platform reference design.
- [Vexless — Serverless Vector Data Management](https://vectordb.ever.works/items/vexless-serverless-vector-data-management) — 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.

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