In this post, I’ll walk you through a T-SQL script that creates application-consistent snapshots on Pure Storage FlashArray, all from within SQL Server, no external tooling. SQL Server 2025 introduces a powerful new feature: the sp_invoke_external_rest_endpoint stored procedure. This enhancement makes calling REST APIs directly from T-SQL easier than ever. Combining this new capability with Pure Storage’s API allows us to orchestrate snapshot operations seamlessly, with no external tools or scripts required.

Ollama SQL FastStart streamlines the deployment of SQL Server 2025 with integrated AI capabilities through a comprehensive Docker-based solution. This project delivers a production-ready environment combining SQL Server 2025, Ollama’s large language model services, and NGINX with full SSL support—all preconfigured to work together seamlessly. I built this project to eliminate the complex configuration hurdles that typically slow down AI integration projects. Whether you’re a database professional wanting to explore SQL Server 2025’s new vector search capabilities or a developer looking to build AI-powered applications on familiar infrastructure, this solution provides everything you need in a single docker-compose file.

With the release of SQL Server 2025, Microsoft is firmly positioning its flagship database platform as an enterprise-ready AI solution. Having spent time with the preview builds and working with the feature set, I believe this release represents a significant opportunity for organizations to leverage AI capabilities and their existing investments in SQL Server infrastructure, skills, and processes. While many cloud-native and niche vector databases have emerged to support AI workloads, SQL Server 2025 brings these capabilities to your existing operational data platform.

As AI continues to evolve, many of us are looking for ways to leverage large language models (LLMs) without relying on cloud services. As we learned in my previous post “Using a Local Large Language Model (LLM): Running Ollama on Your Laptop”, running models locally gives you complete control over your data, eliminates API costs, and can be integrated seamlessly into your existing workflows. Today, I’d like to share how you can interact with local LLMs using PowerShell through the Ollama API.

You can now run powerful LLMs like Llama 3.1 directly on your laptop using Ollama. There is no cloud, and there is no cost. Just install, pull a model, and start chatting, all in a local shell. Large Language Models (LLMs) have revolutionized how we interact with data and systems, but many assume you need significant cloud resources or specialized hardware to run them. Today, I want to walk you through getting started with Ollama, an approachable tool that lets you run large language models locally on your laptop.

In this post, the fifth in our series, I want to illustrate an example of using the T-SQL Snapshot Backup feature in SQL Server 2022 to seed Availability Groups (AGs) with storage-based snapshots. Efficiently seeding an Availability Group is essential for maintaining high availability and ensuring effective disaster recovery. With the introduction of T-SQL Snapshot Backup in SQL Server 2022, snapshots can now be created at the storage layer. This advancement significantly speeds up the initialization of secondary replicas, particularly in environments that handle large databases.

In this post, the fourth in our series, I want to share an example demonstrating SQL Server 2022’s T-SQL Snapshot Backup feature in a scenario where a database spans multiple storage arrays. If you’re dealing with multi-array environments, you’ll appreciate how this technique freezes database write I/O to take coordinated snapshots across volumes on two FlashArrays. In this post, I’ll walk you through the process, point out some of the script’s key elements, and show you how long the write I/O pause takes.

SQL Server 2025 is an upcoming release focused on AI, analytics, and modern database development, backed by innovations in mission-critical engine features for security, performance, and high availability. Let’s dive into what this means for your AI and data-driven applications. We’ll walk through some of the new features announced by Azure Data Principal Architect Bob Ward in his post Announcing SQL Server 2025, and I’ll give some thoughts on these innovations and where they will fit in the enterprise.

In this post, the third in our series on using T-SQL Snapshot Backup, I will guide you through using the new T-SQL Snapshot Backup feature in SQL Server 2022 to take a snapshot backup and then perform point-in-time database restores using that snapshot backup as the base, but this time using an Azure Virtual Machine. We will explore how to manage Azure storage-level operations, such as taking snapshots, cloning snapshots, and executing an instantaneous point-in-time database restore from the snapshot with minimal impact on your infrastructure.

In this post, the second in our series, I will guide you through using the new T-SQL Snapshot Backup feature in SQL Server 2022 to take a snapshot backup and perform point-in-time database restores using a snapshot backup as the base of the restore. We will explore how to manage storage-level operations, such as cloning snapshots and executing an instantaneous point-in-time restore of a database from the snapshot with minimal impact on your infrastructure.