A step-by-step guide for DevOps teams on reviewing, testing, and enforcing policy checks on AI-generated SQL before it ...

How Float achieved 99.3% compression on 1Hz smart meter data with Tiger Data, enabling real-time AI energy analytics, lower ...

This is a performance testing framework for Spark SQL in Apache Spark 2.2+. The framework contains twelve benchmarks that can be executed in local mode. They are organized into three classes and ...

AkasicDB integrates vector, graph, and relational stores within a single DBMS, and processes queries across the three data models as a single execution plan through an unified query planner and ...

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with unstructured content, sales figures alongside customer reviews or citation ...

In addition to delivering quality releases and consistent functionality across these tools and experiences that enable you to efficiently manage and develop with Microsoft SQL Server, we are aiming ...

Every data engineering team right now is being asked the same question: "How do we build a chatbot that talks to our data?" The prototypes are deceptively simple. A developer connects GPT-5.1 to a ...

Your browser does not support the audio element. Hey there, fellow developers! If you've ever dabbled in SQL, you've probably heard the golden rule: "Never use ...

Why is the language developers and DBAs use to organize data such a mess? Here are 13 reasons we wish we could quit SQL, even though we probably won't. For all its popularity and success, SQL is a ...

Abstract: Efficient SQL Query Optimization (QO) is a fundamental aspect of database management systems, aimed at enhancing query performance and reducing resource consumption typically involves ...

Abstract: SQL query optimization (QO) is a critical component of database management systems, essential for improving query execution times, enhancing resource utilization, and ensuring scalability in ...