Azure AI Search stores the data that you query over. Use it as a pure vector index when you need long-term memory or a knowledge base, grounding data for the retrieval-augmented …

In this quickstart, you use a Jupyter notebook to create, load, and query vectors. The code examples perform these operations by using the Azure AI Search client library . The library …

Dec 11, 2025 · Vector Searching (RAG) Relevant source files Purpose and Scope This page documents the Retrieval Augmented Generation (RAG) implementation in the AI Gateway, …

Apr 22, 2025 · Azure offers robust vector database solutions, integrating vector search into its NoSQL, relational, and search platforms. These include Azure Cosmos DB (NoSQL and …

Oct 19, 2023 · Vector databases are engineered to manage vector data, or mathematical constructs that can be depicted in multiple dimensions. They are particularly beneficial in …

Azure AI Search stores vectors at the field level, allowing vector and nonvector content to coexist within the same search index. A search index becomes a vector index when you define vector …

When configuring a pipeline, you can select this Azure AI Search integration as the vector database output. You'll need to specify an index name where Vectorize will write the …

This folder includes the notebooks to demonstrate vector search capabilities of Azure AI Search for text, documents and images using the REST API and Python SDK. Follow the steps to run …

Dec 10, 2025 · The announcement in short Azure HorizonDB is a new fully managed, Postgres-compatible database service introduced in preview. Microsoft positions it for cloud-native …

2 days ago · In this quickstart, you use the Import data (new) wizard in the Azure portal to get started with integrated vectorization. The wizard chunks your content and calls an embedding …