向量数据库 (Vector Database) 是一种专门用于存储和处理向量数据的数据库。向量是一种由数字组成的数组,通常用于表示文本、图像、音频等数据的特征。向量数据库可以快速地搜索和分析向量数据,从而实现相似性搜索、聚类、分类等任务。 向量数据库通常使用基于向量相似性搜索的算法,如 K-近邻搜索、欧几里得距离等。这些...
- [IBM vector database](What is an vector database? | IBM)
A vector database is a type of database that stores data as high-dimensional vectors, which are mathematical representations of features or attributes. Each vector has a certain number of dimensions, which can range from tens to thousands, depending on the complexity and granularity of the data...
Vector Database FAQs A lesser-known data type, vectors, has seized the spotlight recently as an enabler of generative AI. But vectors—and databases capable of storing and analyzing them—have been toiling backstage for many years. They’re used in geospatial mapping and analysis for city planni...
CTO Cloud, DataStax What is a Vector Database? A vector database is a specialized storage system designed to efficiently handle and query high-dimensional vector data, commonly used in AI and machine learning applications for fast and accurate data retrieval. ...
Data consistency, scalability, and performance are critical for data-intensive applications, which is why OpenAI chose to build the ChatGPT service on top of Azure Cosmos DB. You, too, can take advantage of its integrated vector database, as well as its single-digit millisecond response times,...
What is a Vector Database? A vector database is an organized collection of vector embeddings that can be created, read, updated, and deleted at any point in time. Vector embeddings represent chunks of data, such as text or images, as numerical values....
A cloud-native vector database, storage for next generation AI applications golangdistributednearest-neighbor-searchcloud-nativeimage-searchvector-similarityfaissannshnswvector-searchvector-databasellmembedding-databaseembedding-storevector-storeembedding-similaritytensor-database ...
向量数据库是一种以数学向量形式存储数据集合的数据库。向量由一组有序数值组成，表示在多维空间中的位置或方向，可以用于表示复杂对象如单词、图像、视频和音频。在机器学习中，向量用于生成高维度数据，对提升任务如搜索、推荐和内容生成至关重要。向量数据库的兴起主要由大模型 embedding 的应用驱动。
向量化是将不可比较数据转换为向量，利用向量距离关系实现检索功能。通过深度学习模型实现向量化，将不同尺寸、内容的图片或不同长度文本映射到同一向量空间内，相邻向量表示相近语义。向量化主要由模型实现，数据库负责向量存储、更新与版本管理。向量相似度检索是机器学习和模式识别的一个子领域，包括最近邻搜索...