Core Insights - OceanBase has officially launched its first AI-oriented product, PowerRAG, aimed at providing ready-to-use RAG application development capabilities [1] - The company is transitioning into the AI era, focusing on building a data foundation that integrates data and AI capabilities [1][3] - OceanBase's strategy includes enhancing its integrated architecture and introducing a shared storage product that combines object storage with TP databases [1][4] Company Development - OceanBase has evolved from internal technology exploration within Ant Group in 2010 to independent commercialization in 2020, and now actively explores AI applications [2] - The company aims to become a "knowledge base" for enterprises, enhancing vector capabilities and dynamic updates of internal knowledge systems [6] - OceanBase has achieved significant milestones, including over 1,200 ecosystem partners and a community user download exceeding one million [10] AI and Data Relationship - The relationship between AI and data is becoming increasingly critical, with the volume of generated data expected to reach 393.9ZB by 2028 [3] - OceanBase's strategy emphasizes the need for a robust data foundation to support AI applications, addressing challenges such as data acquisition costs and quality assessment [3][4] - The company aims to break down data silos and enhance the integration of various data types through its AI-driven solutions [6] Product Innovations - PowerRAG offers a streamlined development process for RAG applications, addressing issues like long development cycles and high maintenance costs [8] - OceanBase's shared storage product significantly improves cloud data storage elasticity, reducing storage costs by up to 50% under TP loads and to one-tenth under AP loads [9] - The introduction of BQ quantization algorithms has led to a 95% reduction in memory costs for vector scenarios, showcasing OceanBase's commitment to performance and cost efficiency [7][9] Market Opportunities - The cloud database market is projected to grow from over $20 billion in 2024 to over $50 billion by 2028, with public cloud databases expected to account for 70% of the relational database market [11] - OceanBase is positioned to leverage the increasing data demands from industries such as retail, internet, and smart manufacturing, which are experiencing significant growth [11] - The company aims to maintain its focus on data processing while integrating AI, rather than becoming a follower in the AI race [12]

Core Viewpoint - OceanBase is transitioning to an AI-driven era, focusing on integrating data and AI capabilities to enhance its product offerings and market position [1][5]. Group 1: AI Strategy and Product Development - OceanBase has introduced AI-driven products such as PowerRAG, which provides out-of-the-box RAG application development capabilities, facilitating quick development of various AI applications [3][5]. - The company aims to become an integrated data foundation for the AI era, with PowerRAG being the first step in this direction [3][5]. - OceanBase's "shared storage" product allows deep integration of object storage with transactional databases, potentially reducing storage costs by up to 500% [3][4]. Group 2: Market Context and Challenges - The global data generation is expected to reach 393.9 ZB by 2028, driven by technologies like generative AI, presenting significant challenges for data storage, management, and analysis [6]. - The database industry is facing intense price competition, with many companies relying on open-source technologies, leading to low profit margins [7]. - OceanBase acknowledges the importance of cost-effectiveness in the database sector, emphasizing that higher quality often accompanies better pricing strategies [7]. Group 3: Future Outlook and Data Quality - OceanBase is in the early stages of establishing a robust data foundation, which is crucial for future AI applications [6]. - The company recognizes the challenges associated with data quality and availability, which are critical for improving AI model performance [7]. - The integration of enterprise data with AI models is complex, and OceanBase is focused on addressing these challenges through its product offerings [7].

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]