Showing tag results for vectors

We’ve just released major updates to our data access libraries, bringing native support for vector data to both the .NET and JDBC ecosystems, unlocking significant performance gains for AI and machine learning workloads. Microsoft.Data.SqlClient 6.1.0 With the new class, you can now handle vector data in binary format, replacing the slower JSON ...

We are happy to announce that Native vector support in Azure SQL Database and Azure SQL Managed Instance is moving to General Availability this summer. Deployments are already underway, and several regions have begun receiving the feature. What is going GA? Integrated Vector Data Type Azure SQL introduces a dedicated VECTOR data type that simpl...

Storing and querying text embeddings in a database it might seem challenging, but with the right schema design, it's not only possible, it's powerful. Whether you’re building AI-powered search, semantic filtering, or recommendation features, embeddings, and thus vectors, are now a first-class data type. So how do you model them well inside a databa...

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 t...

In the previous article of this series, it was discussed how embeddings can be quickly created from data already in Azure SQL. This is a useful starting point, but since data in a database changes frequently, a common question arises: “How can the vectors be kept updated whenever there is a change to the content from which they have been generated?...