Qdrant, the leading provider of high-performance, open source vector search, is debuting Qdrant Cloud Inference, a new solution for generating text and image embeddings directly within managed Qdrant ...

We save the title, a chunk from the body, and the embedding vector for the chunk in a row of the database. For each article, there are as many vectors as there are chunks. We index the vector ...

It also claimed that it achieved about 39% faster search speed than pgvector’s ierarchical navigable small world (HNSW) algorithm and 363% faster search speed than pg_embedding. “Timescale Vector ...

The announcement of S3 Vectors has sparked intense discussion, with some speculating that it could disrupt the vector database market.

Qdrant Cloud Inference simplifies building applications with multimodal search, retrieval-augmented generation, and hybrid ...

Just a few “native” vector databases existed prior to ChatGPT, such as Pinecone, Milvus, and Zilliz.But almost overnight, many existing database vendors adapted their wares to be able to store, index, ...

A vector database doesn’t rely on tags, labels, metadata or other tools typically used to structure data. Instead, because a vector embedding can track any property we deem relevant, vector ...

Data platform vendor DataStax is entering the vector database space, announcing the general availability of vector search in its flagship Astra DB cloud database.. DataStax is one of the leading ...

Generative AI Fueling A Fast-Growing Market. The global vector database market is expected to expand rapidly, from $1.5 billion last year to $4.3 billion by 2028, driven in large part by the expanding ...

Implement vector databases: Set up a vector database to store your data's embedded representations. This database will serve as the backbone of your RAG system, enabling efficient and accurate ...