Zuhause bei Freunden: Torsten Strauß on exciting SQL Server 2025 features

** Dear Monster and Monster friends, **
On September 10th, an old friend of the Berlin DataTonster comes to the capital. Torsten Strauss will talk about an exciting feature in the upcoming SQL Server 2025. Anyone who knows Torsten knows that an exciting, technically profound lecture awaits us here. Experience has shown that to be there on site is even more worthwhile with Torsten than participating online. So take the time, come over and bring your colleagues with them.

Markus and Ben are happy

We carry out this meeting hybrid, you can [here ] (https://teams.microsoft.com/l/meetup-join/19%3ameeting_odmwwyzoditmge1ni00njviltg0ztg5ntyynzexzgq1%40thread.v2/0?contex T =%7b%22Id%22%2240dee412-4d0f-42cf-8aad-aad-aad-aad-a22F61F4948%22%22oid%3A%222d576807-9bfd-2FC5FD7C1C1C1C6A) online) online participate.
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** Dear Monsters and Monster Friends, **
On September 10, to Old Friend of the Berlin Data Monsters is coming to the capital. Torsten Strauß wants to speak about exciting feature in the upcoming SQL Server 2025. Anyone Who Knows Torsten Knows that we can look forward to a fascinating, Technicalally in-Depth Presentation. Based on Past Experience, attending in person is even more Worthwhile with Torsten Than Joining Online. So take the time, come by, and bring your Colleagues along as well.
Looking forward to seing you,

Markus and Ben

This is a hybrid event, you can join [here] (https://teams.microsoft.com/l/meetup-Join/19%3ameeting_odmwwyzoditmge1ni00njviltg0ztg5ntyynzexzgq1%40thread.v2/0?c ontext =%7b%22%22%2240dee412-4d0f-42cf-8aAd-aad-aad-aad-aad-a22f61f4948%2C%22oid%222d576807-4f34-9bfd-2FC5FD7C1C1C6A%7d).

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** Session and speaker: **
Next-gen ai insights native vector search in SQL Server 2025

SQL Server 2025 Extends Your Existing Data Platform with a native Vector Search, Enabling Ai-Powered Similarity Queries Directly Within the Database. New Vector Data Types and Built-in Index Structures Allow You To Efficient Store and query high-dimensional embeddings (e.G., from NLP or Image Models). Thanks to Optimized Approximate Nearest Neiighbor Algorithms, You’ll Achieve Villise Cond-Level Response Times-Even with Millions of Vectors.
This feature Unlocks A Variety of Use Cases: You Can Implement Real-Time Personalized Recommendations for E-Commerce, Semantics Analytics On Text Or Image Data, Or Anomaly-Based Security Scans Without For An External Search Infrastructure. Seamless Integration with Azure Hybrid Scenarios So Lets You Scale Your Vector Searches Both On-Premises and In The Cloud. All of this Runs on your Proven SQL Platform, Complete with Role-Based Access Control and Always Encrypted Support for Sensitive Embeddings.

** Torsten Strauß **
Torsten (MVP, MCSE, MCT) has been working with Microsoft SQL Server Sion of the Turn of the Millennium and Specializes in Performance Optimization for Large SQL Server Environment.
He has been with bp for over two decades in Various Roles and is Currently Employed as a Senior Software Engineer. Addition, He Collaborates Closely with Sarpedon Quality Lab As a Principal Consultant for Microsoft SQL Server.
Torsten has delivered more than 250 Presentations on Microsoft SQL Server Performance Optimization at National and International Conferences and User Groups.
Since 2018, Torsten has been recognized as a Microsoft Most Valuable Professional for Data Platform.