The ability to write parts of SQL queries in natural language will help developers speed up their work, analysts say.

In 2026, contextual memory will no longer be a novel technique; it will become table stakes for many operational agentic AI deployments. At the beginning of the modern generative AI era, purpose-built ...

DB-GPT-Hub is an experimental project to implement Text-to-SQL parsing using LLMs, which mainly includes dataset collection, data pre-processing, model selection and construction, and fine-tuning ...

OpenJDK project teams will focus work on features such as value types, code reflection, AOT compilation, and structured ...

The world tried to kill Andy off but he had to stay alive to to talk about what happened with databases in 2025.

Think back to middle school algebra, like 2 a + b. Those letters are parameters: Assign them values and you get a result. In ...

Abstract: Text-to-SQL conversion, the process of generating SQL queries from natural language input, has gained significant attention due to its potential to simplify database interaction. Although ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Abstract: This paper introduces a Chain-of-Thought prompting framework for Text-to-SQL tasks, incorporating coverage and redundancy feedback to tackle missing or redundant query conditions. It breaks ...

Spider is a large human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task (natural language interfaces for relational databases). It is released along with our EMNLP ...