工程化的长期主义：OceanBase十五年沉淀，如何成为AI时代的数据基石？

Core Insights - The rapid development of artificial intelligence (AI) is transforming databases from passive "data warehouses" to active "intelligent hubs" that drive business decisions [2] - OceanBase has launched its first AI-native hybrid search database, seekdb, aiming to transition databases from traditional "business support systems" to "AI-native data entry points" [4] - OceanBase's engineering capabilities are a key factor in its success, with over 4,000 clients and an average annual growth rate of over 100% in client numbers for five consecutive years [2][4] Engineering Evolution - OceanBase's 15-year journey has been driven by real business pressures, leading to a unique engineering culture focused on solving practical problems [5][7] - The company has achieved several key technological milestones, including the establishment of a native distributed architecture and the breakthrough of a single-node distributed integrated architecture [8] - The latest version, 4.4, integrates transaction processing (TP), analytical processing (AP), and AI capabilities into a single core, allowing businesses to handle high-concurrency transactions, complex data analysis, and AI-driven hybrid searches within one database [8][11] Architectural Innovations - OceanBase emphasizes data correctness as a core principle, implementing a comprehensive system for end-to-end control from code to hardware [10] - The architecture supports multi-modal data integration and workload fusion, addressing challenges posed by traditional database systems in the AI era [11][12] - The introduction of a shared storage architecture in version 4.4 significantly reduces storage costs by 50%-90% compared to traditional solutions, enhancing the efficiency of data storage for AI applications [12] AI-Native Capabilities - The seekdb database is designed with a focus on lightweight, agile, and open-source principles, featuring a four-dimensional hybrid search capability [13][15] - OceanBase's AI architecture allows for direct SQL calls to embedding models, creating a closed loop for data writing, vectorization, retrieval, and inference [16] - The company aims to redefine the standards for AI data bases, moving beyond traditional data storage to databases that can "understand" data semantics [16] Market Position and Future Outlook - OceanBase holds the leading market share in the financial sector, with significant deployments in government and telecommunications [17][19] - The company is actively pursuing global expansion, targeting emerging markets in Southeast Asia, Latin America, and the Middle East, with a goal of increasing overseas revenue to 20% [19] - According to Gartner, spending on databases supporting generative AI is projected to reach $218 billion by 2028, indicating a significant market opportunity for OceanBase [20]