Tag: hybrid search
Plataforma única, Couchbase multiuso: Pesquisa vetorial, geoespacial, SQL++ e muito mais
Há casos de uso que são melhor atendidos por vários tipos de acesso a dados, incluindo SQL, pesquisa vetorial, consultas geoespaciais e acesso de valor-chave. Uma abordagem é combinar/encadear vários sistemas de dados para cada método de acesso. No entanto,...
Single Platform, Multi-Purpose Couchbase: Vector Search, Geospatial, SQL++, and More
There are use cases that are best served by multiple types of data access, including SQL, vector search, geospatial queries, and key-value access. One approach is to combine/chain together multiple data systems for each access method. However, the Couchbase approach...
What are Embedding Models? An Overview
What are embedding models? Embedding models are a type of machine learning model designed to represent data (such as text, images, or other forms of information) in a continuous, low-dimensional vector space. These embeddings capture semantic or contextual similarities between...
Querying Vectors And Things That Can Go Wrong With Them
Couchbase 7.6 introduces Vector Search into the Couchbase architecture, expanding its search capabilities by leaps and bounds. This article showcases how this affects search queries, how we have to adapt in certain situations and how to efficiently use this latest...
Hybrid Search: An Overview
What Is Hybrid Search? Hybrid search typically refers to a search approach that combines multiple search methodologies or technologies to provide more comprehensive and accurate results. In the context of information retrieval, hybrid search often involves blending traditional keyword-based searching...