As SQL Server 2016 approaches end of support in July 2026, a look back at its groundbreaking innovations reveals how it reshaped Microsoft's data platform and why it's time to move forward.

I’ve spent a lot of time inside enterprise AI deployments, and one thing that has become clear is that IT departments are ...

As fintech platforms grow, the mix of performance tuning and security oversight becomes harder to manage manually. Systems ...

An evolving method of hiring for labour in India is through a structural reform in the hiring landscape, with the gradual ...

Progress Software Corporation ( PRGS) Discusses High-Performance Multi-Database Connectivity and WinSQL Features May 7, 2026 1:00 PM EDT ...

Dell Technologies World 2026 keynote: why time to token and cost per token are now the essential metrics for enterprise AI ...

For most enterprise applications, vector support is a feature that should be woven into the existing data estate, not a ...

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private ...

Web applications rely on multiple layers of infrastructure to process user requests efficiently. Load balancers, reverse proxies, caching servers, and application servers all work together to improve ...

We’re talking past each other because our tech vocabulary is outdated; we need specific labels to separate valuable AI work from total slop.

Andy MacMillan thinks business analysts, not IT and not the vendors, should own the layer where enterprise AI gets its ...

Microsoft’s Azure-based AI development and deployment platform shines with a strong selection of models and agent types and an excellent playground for experimenting with agents.