AnDB用AI原生技术实现结构化与非结构化数据统一语义查询
AnDB: Breaking Boundaries with an AI-Native Database for Universal Semantic Analysis
- 通过AI原生架构支持语义级SQL查询，无需用户懂AI
- 自动生成并优选执行计划，平衡准确率、速度与成本
- 适合需要跨数据类型分析的开发者与数据工程师
本文展示AnDB——一种AI原生数据库，既能处理传统OLTP负载，又能支持AI驱动任务，实现对结构化与非结构化数据的统一语义分析。当前结构化数据分析成熟，但用户查询与非结构化数据间仍存在语义鸿沟。AnDB利用前沿AI技术，让用户以直观的SQL-like语句进行语义查询，无需具备AI知识。该方法避免了传统文本转SQL系统的歧义性，并提供端到端优化能力。AnDB通过其优化器自动生成多个执行计划，并根据用户策略与内部机制，在准确性、执行时间和财务成本之间进行权衡，选择最优方案。该系统为数据管理基础设施提供未来兼容性，使用户无需从零开始即可高效挖掘各类数据价值。
原文摘要 · Abstract (English)
In this demonstration, we present AnDB, an AI-native database that supports traditional OLTP workloads and innovative AI-driven tasks, enabling unified semantic analysis across structured and unstructured data. While structured data analytics is mature, challenges remain in bridging the semantic gap between user queries and unstructured data. AnDB addresses these issues by leveraging cutting-edge AI-native technologies, allowing users to perform semantic queries using intuitive SQL-like statements without requiring AI expertise. This approach eliminates the ambiguity of traditional text-to-SQL systems and provides a seamless end-to-end optimization for analyzing all data types. AnDB automates query processing by generating multiple execution plans and selecting the optimal one through its optimizer, which balances accuracy, execution time, and financial cost based on user policies and internal optimizing mechanisms. AnDB future-proofs data management infrastructure, empowering users to effectively and efficiently harness the full potential of all kinds of data without starting from scratch.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。