Vector Similarity Search with Azure SQL database and OpenAI
Vector databases are gaining quite a lot of interest lately due to the fact that using text embeddings and vector operations it is very easy to find similar “things”. Things can be articles, photos, products…everything. As one can easily imagine, this ability is great to easily implement suggestions in applications.
The post Vector Similarity Search with Azure SQL database and OpenAI appeared first on Azure SQL Devs’ Corner.
Published on:
Learn moreRelated posts
Azure Function | Publish | ‘attempt to publish the ZIP file failed’ error
While publishing a C# Azure Function from Visual Studio, I encountered the following error: The attempt to publish the ZIP file through XXXXX ...
Azure SDK Release (March 2025)
Azure SDK releases every month. In this post, you find this month's highlights and release notes. The post Azure SDK Release (March 2025) appe...
MWC 2025 Azure Foundry
New Overlapping Secrets on Azure DevOps OAuth
As you may have read, Azure DevOps OAuth apps are due for deprecation in 2026. All developers are encouraged to migrate their applications to ...
Azure Cosmos DB Conf 2025: Learn, Build, and Connect with the Community
Join us for the 5th annual Azure Cosmos DB Conf, a free virtual developer event co-hosted by Microsoft and the Azure Cosmos DB community. This...
Summer 2025 Dynamics 365 Maps Release: Smarter Routing, Azure Maps, Canvas Apps & More!
Technology never stands still, and neither does Team Maplytics! With our latest March 2025 updates, your geo-mapping experience within Dynamic...
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 applica...