The purpose of the Text-to-SQL task is to bridge the gap between natural language and SQL queries. Current approaches mainly rely on large language models (LLMs), but employing them for Text-to-SQL ha ...

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Abstract: Privacy-preserving collaborative data analysis is a popular research direction in recent years. Among all such analysis tasks, privacy-preserving SQL ...

Abstract: The Text-to-SQL task has significant application prospects in automating relational database query interfaces. It can reduce user learning costs and improve data query efficiency. However, ...

The ability to write parts of SQL queries in natural language will help developers speed up their work, analysts say. Google is previewing a new AI-driven feature in its BigQuery data warehouse that ...

A small, in-memory SQL query engine implemented in Python. It loads CSV files into memory, parses a small subset of SQL, executes queries (projection, filtering, simple aggregation), and exposes a ...

In this tutorial, we build an advanced Agentic Retrieval-Augmented Generation (RAG) system that goes beyond simple question answering. We design it to intelligently route queries to the right ...

The Visual Query Builder in DBeaver is a visual tool that helps you build and understand SQL queries in complex databases. It lets you work with your database in a visual way, making it easy to see ...

MS SQL Server: Learn from Scratch – Build and manage databases, write queries, and navigate SQL Server Management Studio like a pro. SQL Server Backup & Recovery – Protect data with full, differential ...

A new SQL Server 2025 feature lets organizations run vector-based semantic searches on their own data, connecting to local or cloud-hosted AI models without relying on massive general-purpose LLMs. I ...