Vector Search with Azure SQL, Semantic Kernel and Entity Framework Core

Vector databases like Qdrant and Milvus are specifically designed to efficiently store, manage, and retrieve embeddings. However, many applications already use relational databases like SQL Server or SQL Azure. In such cases, installing and managing another database can be challenging, especially since these vector databases may not offer all the features of a modern relational […]
The post Vector Search with Azure SQL, Semantic Kernel and Entity Framework Core appeared first on Azure SQL Devs’ Corner.
Published on:
Learn moreRelated posts
NVIDIA NIM on Azure AI Foundry
Upcoming Updates for Azure Pipelines Agents Images
To ensure our hosted agents in Azure Pipelines are operating in the most secure and up-to-date environments, we continuously update the suppor...
TLS 1.3 support in Azure Cosmos DB
This article follows announcement on a previous article that mentioned the end of support for Transport Security Layer (TLS) 1.0/1.1. TLS 1.3 ...
Power Pages | Azure AD B2C | Claims mapping
In my previous blog post : [Step by Step] Power Pages : Set up Azure AD B2C I explained the steps to set up Azure AD B2C tenant and configure ...
Azure Data Factory: Read CSV file, Transform and push data to Dataverse
Let’s try to create a simple scenario that we can do in Azure Data Factory! Azure Data Factory is a serverless data integration service ...