February 2026
Intermediate to advanced
48 pages
23m
Chinese
Overview
本作品已使用人工智能进行翻译。欢迎您提供反馈和意见：translation-feedback@oreilly.com
随着人工智能系统从无状态提示发展到自主、感知上下文的代理，企业基础设施正面临着新的考验。挑战不仅在于计算，还在于内存。智能系统现在需要对大量相互关联的数据进行检索、调用和推理，同时保持速度、一致性和可解释性。代理人工智能数据架构》探讨了分布式 SQL 如何在这个新时代重新定义数据层，为大规模结构化、语义和时间检索提供统一的方法。
本报告专为数据架构师、人工智能基础架构工程师和技术领导者撰写，为构建支持代理人工智能应用的耐用、高性能内存系统提供了可行的指导。通过真实世界的设计模式--包括 RAG 管道、长期内存图以及混合事务和操作架构--它展示了分布式 SQL 如何作为人工智能原生数据基础架构的基础。
- 了解为什么内存而非计算是代理人工智能的新限制因素
- 将结构化数据、向量数据和历史数据整合到一个检索层中
- 在分布式 SQL、向量存储和混合堆栈之间进行权衡比较
- 为持久性和上下文人工智能工作负载设计可扩展性架构
- 使企业数据基础设施现代化，以支持智能自适应系统
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