Showing tag results for RAG

If you work with Microsoft SQL regularly, the AI conversation right now probably feels a little exhausting. Every week brings a new platform, a new pattern, a new opinion about how you’re “supposed” to build AI apps. Most of it assumes you’ll start over. You don’t have to. We’re running SQL AI App in a Day workshops with Microsoft partners ar...

We are happy to share that DiskANN vector indexing is now in public preview across Azure SQL Database, Azure SQL Managed Instance, and SQL database in Microsoft Fabric. DiskANN is a cutting-edge algorithm for efficient vector similarity search, making it ideal for powering recommendation systems, image and multimedia search, and advanced retrieval-...

SQL Server 2025 marks a major milestone in database innovation by introducing native support for VECTOR data types and vector functions. These are now fully available in the freshly released SQL Server 2025 RTM. This means you can store and process high-dimensional embeddings directly within your database. It eliminates the need to move data acr...

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...

Today, more and more customers are embracing AI with one clear goal in mind: they want to chat with their data. And by "data," they mean all of it:  structured tables, unstructured documents, images, audio, and more. This demand has given rise to hybrid approaches that blend semantic understanding with precise data retrieval. But here’s the chal...

Back in the earlier part of the year (February maybe?), I put this tutorial together for our early adopters in the SQL Server 2025 program. It’s a guide for setting up SQL Server 2025 in a Hyper-V VM (I used Windows Server) with Ollama and ngnix as an https proxy. It's a variation of my workshops for Ignite 2024 and a SQL in Fabric one from Februar...

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...

The RAG (Retrieval Augmented Generation) pattern, which is commonly discussed today, is based on the foundational idea that the retrieval part is done using vector search. This ensures that all the most relevant information available to answer the given question is returned and then fed to an LLM to generate the final answer. While vector search...

Public Preview of Native Vector Support in Azure SQL Database We are excited to share that the dedicated vector data type in Azure SQL Database, which was previously available through the Early Adopter Preview, is now transitioning to Public Preview! As of today, the Vector data type and its associated functions are accessible to everyone, autom...

RAG - Retrieval Augmented Generation - is by far one of the most common patterns today as it enables the creation of chatbots that can chat on your own data, as I described in my previous "Retrieval Augmented Generation with Azure SQL" blog post. As soon as you start to use it excitement grows, as it provides a sort of a magical experience. Experie...