Group 1 - The demand for cloud databases has surged due to the need to handle massive amounts of unstructured data in generative AI applications [1][2] - OceanBase's cloud database product, OB Cloud, has served over 200 leading retail enterprises in various sectors, including apparel, food service, fast-moving consumer goods, and direct-to-consumer [1] - The retail industry is shifting from broad traffic operations to deep user value exploration, with over 90% of enterprises believing AI will significantly enhance productivity [1] Group 2 - OceanBase, founded in 2010, launched its integrated cloud database platform OB Cloud in 2022, aiming to assist various industries in transitioning to a digital intelligence era [2] - OB Cloud utilizes technologies like vector fusion queries to enable deep understanding of unstructured data such as images, videos, and text comments, facilitating features like image search and intelligent product recommendations [2] - The "Integrated Cloud Database White Paper" released at the conference emphasizes the transition of integrated cloud databases from "cost centers" to "growth engines," highlighting the need for companies to focus on six dimensions for technology selection [2]

Core Insights - The retail industry is undergoing a transformation where data infrastructure is shifting from a "cost center" to a "growth engine" [1] - Over 90% of enterprises believe that generative AI will enhance productivity, but traditional architectures face challenges such as data latency and system fragmentation [1][3] - A robust data foundation is essential for supporting real-time decision-making and AI applications in retail [4] Group 1: Industry Trends - Retail has moved from extensive traffic operations to deep user value exploration, with AI integrated across the entire supply chain [1] - The need for a data foundation that can handle "pulse-like surges" in traffic and serve as a "real-time decision engine" is critical [3][4] - The competition in retail is fundamentally about the capabilities of the data foundation, emphasizing the importance of ecosystem collaboration [5] Group 2: Technological Advancements - OceanBase's HTAP foundation has enabled companies like Haidilao to streamline their membership operations and achieve personalized recommendations [3] - The OB Cloud platform has reduced scaling time by 90% for companies like Pop Mart, allowing them to handle a hundredfold increase in traffic with high availability [3] - OB Cloud is focusing on deep integration of AI with databases, enhancing the understanding of unstructured data such as images and text [4] Group 3: Market Impact - OceanBase has served over 200 leading retail clients across various sectors, demonstrating the scalability of its solutions [4] - The global expansion of OB Cloud has reached over 50 regions, with a customer growth rate of 130%, showcasing the adaptability of Chinese technology [5] - The future of retail efficiency and innovation may be redefined as more companies adopt these transformative technologies [5]

Core Insights - The retail industry is facing dual challenges of fluctuating traffic and AI transformation, necessitating a stable and efficient data foundation for success [1][3] - OceanBase Cloud (OB Cloud) aims to deepen its presence in the new retail sector by providing integrated cloud database solutions [1][4] Industry Trends - The retail sector is shifting from broad traffic operations to deep user value exploration, with over 90% of companies believing that generative AI will enhance productivity [3] - Traditional architectures face issues such as data latency and system fragmentation, hindering real-time decision-making and AI innovation [3] Company Developments - OB Cloud has developed four core capabilities to address retail challenges: integration of transaction and analysis, multi-model data fusion, vectorized query for AI applications, and multi-cloud native deployment [4] - The platform has demonstrated significant performance improvements, such as a 90% reduction in scaling time for high traffic scenarios and a 45% increase in real-time computing power for member systems [4][5] Case Studies - Haidilao utilized OB Cloud to manage high concurrency in its membership system, achieving stable operations that support over 80% of its total revenue [4][6] - The integration of OB Cloud in Haidilao's inventory system allows for real-time stock calculations and proactive decision-making, reducing response time from days to minutes [5] AI Integration - OB Cloud is focusing on deep integration of AI with databases, enhancing capabilities to understand unstructured data such as images and text [6] - The platform enables features like visual search and intelligent recommendation systems, improving customer experience and operational efficiency [6] Market Position - OB Cloud has served over 200 leading retail enterprises, including Li Ning and Haidilao, and is becoming a key infrastructure for the digital transformation of the retail industry [6][7] - The company has established a global presence across more than 50 regions, with a customer growth rate of 130% [7] Research Insights - A white paper released at the conference highlights the transition of integrated cloud databases from cost centers to growth engines, emphasizing the need for businesses to focus on architecture design and AI capabilities [7]

Core Insights - The first "2025 Retail Data Foundation Innovation Conference" was held in Shanghai, co-hosted by OceanBase, IT Dongfanghui, and EFCIO, where the "Integrated Cloud Database White Paper" was released, marking the first systematic exposition of integrated cloud database value in the retail industry [1] - The white paper emphasizes that in the era of "second-level decision-making" and "centimeter-level insights," integrated cloud databases are transitioning from being a "cost center" to a "growth engine" [1] - Retail enterprises are encouraged to focus on six dimensions for technology selection: architecture design, cost-effectiveness balance, high availability, IT integration capability, security compliance, and AI-native capabilities to establish a solid foundation for the new retail integrated data base in the AI era [1] Industry Challenges - The retail industry is facing dual challenges of pulse-like traffic shocks and AI transformation, necessitating a stable, efficient data foundation that supports AI applications as a key to success [2] - Over 90% of surveyed enterprises believe that generative AI will enhance productivity, yet traditional architectures suffer from data delays, system fragmentation, and resource redundancy, hindering real-time decision-making and AI innovation applications [2] - The retail sector's next competitive round is fundamentally about the capability of the data foundation, which requires a new generation of technology base that meets "full-time response, full-domain coverage, full-end adaptation, and full-staff collaboration" [2]

新华财经上海8月28日电（记者王淑娟）生成式人工智能应用需处理海量非结构化数据，带动了市场对 云数据库的需求激增。在28日举办的首届"2025零售数据底座创新大会"上，记者从国产原生分布式数据 库OceanBase（海扬数据库）获悉，近两年来，其云数据库产品OB Cloud已服务李宁、安踏、海底捞、 泡泡玛特等200余家头部零售企业，覆盖鞋服、餐饮、快消、商超、DTC（直达消费者）新经济等全零 售业态，实现规模化落地。 中国连锁经营协会行业创新部主任田芮丰在会上表示，零售行业已从粗放流量运营转向用户价值的深度 挖掘，AI贯穿"研、产、供、销、服"全链路。超九成企业认为生成式AI将提升生产力，但传统架构存在 数据延迟、系统割裂、资源冗余等问题，难以支撑实时决策与AI创新应用。 OceanBase 首席执行官杨冰认为，零售行业数智化转型面临着三大核心挑战：如何驾驭流量"脉冲式爆 发"、如何让数据成为"实时决策引擎"、以及如何让AI从"锦上添花"变为"基础设施"，这也是海扬数据 库与众多客户共同攻坚的方向。零售行业亟需满足"全时响应、全域覆盖、全端适配、全员协同"的新一 代技术底座，而一体化云数据库是破局的关键。 ...

Core Viewpoint - The article emphasizes the challenge of integrating AI into core business operations, highlighting that while powerful foundational models exist, the real difficulty lies in their practical application to create value [1][2]. Group 1: AI Integration Challenges - Many enterprises face a collective dilemma where models are easily accessible, but implementation remains challenging [2]. - The bottleneck for enterprises in AI deployment is not the models themselves but rather the integration of AI into existing business processes [16][17]. - Key obstacles include the adaptation of technology to various business scenarios and the balance between cost and performance [14][15]. Group 2: OceanBase's AI Solutions - OceanBase has launched its cloud database product, OB Cloud, which has successfully integrated AI capabilities and achieved significant deployment across various industries [3][4]. - OB Cloud has enabled numerous leading companies in sectors such as e-commerce, logistics, and education to transition AI applications from concept to reality [4][18]. - The platform supports a unified architecture that allows for the simultaneous handling of transactional processing, real-time analysis, and AI workloads without the need for additional technology stacks [25][27]. Group 3: Advantages of OB Cloud - OB Cloud is built on major public cloud infrastructures, providing a multi-cloud native advantage that allows for global scalability and flexibility [20][22]. - The platform's integrated architecture facilitates real-time insights and reduces the complexity of data processing, making it easier for enterprises to leverage AI [30][31]. - OB Cloud offers out-of-the-box products like PowerRAG, which simplifies the implementation of AI-driven solutions, thus lowering the barriers for enterprises to adopt AI technologies [32][33]. Group 4: Future of Cloud Databases and AI - The integration of cloud databases and AI is becoming essential for enterprises undergoing digital transformation, with a shift from traditional storage roles to intelligent data engines [36][39]. - The article suggests that the future of cloud databases lies in their ability to handle multi-modal data and support intelligent computing needs, positioning them as ideal solutions for AI deployment [45][46].

Core Insights - OceanBase is evolving from an integrated database to an integrated data foundation, focusing on Data×AI capabilities to address new data challenges in the AI era [1][2][4] - The company launched PowerRAG, an AI-driven application product that provides ready-to-use RAG (Retrieval-Augmented Generation) application development capabilities [1][5][7] - OceanBase introduced a new "shared storage" product that integrates object storage with transactional databases, significantly reducing storage costs by up to 50% for TP loads [9][10] AI Strategy and Product Development - OceanBase aims to support mixed workloads (TP/AP/AI) through a unified engine, enhancing SQL and AI hybrid retrieval capabilities [2][4] - The PowerRAG service streamlines the application development process by connecting data, platform, interface, and application layers, facilitating rapid development of various AI applications [5][7] - The company is committed to continuous breakthroughs in application and platform layers to solidify its position as an integrated data foundation in the AI era [5][7] Performance and Infrastructure - OceanBase has achieved leading performance in vector capabilities, essential for supporting AI applications, and is continuously optimizing vector retrieval algorithms [8][9] - The latest version of OceanBase enhances mixed retrieval performance through advanced execution strategies and self-developed vector algorithm libraries [9] Shared Storage Innovation - The "shared storage" product represents a significant architectural upgrade, allowing for deep integration of object storage with transactional databases, thus improving cloud data storage elasticity [9][10] - This innovation positions OceanBase's cloud database, OB Cloud, as the first multi-cloud native database to support object storage in TP scenarios, catering to various business applications [10]