AI不接受碎片化的数据世界。 这是近期一项最新研究得出的结论——如果AI模型长期接触高流行但低价值的碎片化数据，会出现类似人类"脑损伤"的现象。 在一体化的数据世界，我们需要AI原生一体化的数据库。当"AI+"走向"AI原生"，AI不再是一个零散的附加功能，而是系统架构的核心方向，对于数据库 而言更是如此。 数据库正成为AI的"第二战场" "AI的真正瓶颈不在模型，而在数据。"这是杨冰与OceanBase对AI原生时代的技术判断。 在过去两年生成式AI带来的技术革命中，大模型训练集中于算法模型与算力建设，然而，随着推理模型的深度应用，开发者与企业都逐渐意识到，私有 化数据才是AI真正的"护城河"。这里形成的数据"护城河"有两方面，一是数据本身的质量与模型对数据的理解，二是调用数据的效率。 MIT Project NANDA最新研究显示，95%的企业在生成式AI投入生产后，仍然没能看到可以衡量的回报，其主要原因在于多模态数据割裂、系统链路冗 长、权限管理复杂难以落地，导致模型无法持续理解业务上下文、缺乏实时适应能力。 以往割裂的系统架构使得传统碎片化的数据查询分析，难以适应AI时代的需求。一方面，过去向量数据、 ...

Core Viewpoint - The article emphasizes the necessity for integrated data systems in the AI era, highlighting that fragmented data can hinder AI performance and lead to inefficiencies. The focus is on creating an "AI-native integrated" database that supports real-time analysis and intelligent applications [1][6][10]. Group 1: AI Native Database Development - OceanBase launched its first AI-native hybrid search database, "seekdb," which allows developers to build knowledge bases and AI applications with just three lines of code, enabling efficient handling of multi-modal data retrieval at a scale of billions [2][4]. - The CEO of OceanBase stated that "seekdb" is not merely an addition of traditional database functions but a restructured database specifically designed for the AI era, aiming to be a real-time entry layer for large models and private data integration [4][10]. Group 2: Challenges in AI Implementation - A recent MIT study revealed that 95% of enterprises did not see measurable returns after implementing generative AI, primarily due to fragmented multi-modal data and complex system linkages, which hindered the models' ability to understand business contexts [7]. - Traditional fragmented systems are inadequate for AI demands, as they complicate cross-system queries and real-time responses, necessitating a shift towards integrated data management systems [7][8]. Group 3: OceanBase's Strategic Response - OceanBase's strategy involves a deep integration of four core capabilities: unified multi-modal data management, multi-workload support, native AI function capabilities, and hybrid multi-cloud deployment, all aimed at creating a modern data architecture that supports AI [10][11]. - The company aims to ensure that its database can handle various data types and workloads simultaneously, providing a seamless experience for developers and businesses [11][12]. Group 4: Market Performance and Growth - Since its commercialization in 2020, OceanBase has reported over 4,000 global customers, with an average annual growth rate exceeding 100% for five consecutive years, indicating strong market demand [15][18]. - The company has expanded its cloud services across major platforms like Alibaba Cloud, AWS, and Azure, supporting a "one architecture, global operation" model for Chinese enterprises [16][21]. Group 5: Ecosystem and Collaboration - OceanBase emphasizes the importance of ecosystem growth, with over 70% of its revenue coming from partners and an annual growth rate of 80% in the private cloud sector [21][22]. - The company collaborates with over 350 ISVs to create standardized solutions across various industries, enhancing its market presence and operational efficiency [22][23].

Core Insights - The digital transformation of financial institutions is entering a critical phase, with a consensus on adopting distributed databases for core systems [1][4] - OceanBase has achieved its "Hundred Banks Plan," providing database services for over 190 core systems and more than 1,000 key business systems across over 100 banks [1][4] Industry Trends - Financial institutions require a tripartite synergy of policy guidance, technology drive, and market demand for core system upgrades, emphasizing higher demands for security, stability, and scalability of data infrastructure [4] - The essence of digital transformation in financial institutions is to leverage data to reshape traditional business and organizational models, thereby building new competitive advantages [4] Company Developments - OceanBase, a 100% self-developed native distributed database, has scaled its services from leading financial core systems to mid-tier financial institutions, supporting various types of financial entities such as banks, insurance, and securities [4] - In May, OceanBase set a record for efficiency in switching 133 systems in 48 hours for Sichuan Bank, enhancing its IT infrastructure to a high availability level [5] - OceanBase has implemented integrated database solutions that address challenges faced by financial institutions, achieving a unified approach to data management [5] Product Innovations - OceanBase launched version 4.4.0 at the financial exhibition, enhancing transaction processing, real-time analysis, and AI-native capabilities to meet the needs of financial institutions in AI scenarios [6] - China Pacific Insurance is the first major insurance company to upgrade all core systems to OceanBase, exploring new capabilities such as AI for database fault diagnosis [5][6]