As a crucial component of data infrastructure, database technology is undergoing a pivotal transformation from a "quantity-oriented" to a "quality-oriented" phase. In the future, database technology innovation, talent cultivation, ecosystem construction, and application implementation will be the key drivers of digital economic development.
Vector Databases: Enhancing the retrieval efficiency of unstructured data and supporting the rapid development of artificial intelligence.
Multi-Model Databases: Supporting multiple data models to reduce the complexity of database operations.
Fully Homomorphic Encrypted Databases: Providing encryption throughout the entire data lifecycle to ensure data security.
Spatio-Temporal Databases: Enhancing the ability to integrate, query, and analyze massive spatio-temporal data such as raster and point cloud data.
Bidirectional Empowerment of AI and Databases
AI for DB: Utilizing AI technologies to optimize database operations and maintenance, reducing operational thresholds, and enabling self-management and operation of databases.
DB for AI: Supporting the deployment of large language models with database technology, improving retrieval accuracy, and facilitating efficient AI modeling.
Industry Applications of Databases
Financial Industry
The application of databases in the financial industry exhibits a coexistence of centralized and distributed systems, with open-source databases gaining widespread adoption. The deepening application of database technology in the financial industry has driven innovative developments in financial services.
Telecommunications Industry
The telecommunications industry has seen an increased demand for diversified databases, which play a crucial role in billing systems, real-time information queries, and cloud storage services. The application of database technology has enhanced the service capabilities and operational efficiency of the telecommunications industry.
Manufacturing Industry
In the digital transformation of the manufacturing industry, database technology plays a pivotal role in data integration and sharing, industrial chain collaboration, and data asset management. Cloud-edge-device collaborative distributed multi-model databases, for instance, cater to the manufacturing industry's need for managing massive heterogeneous data.
Energy Industry
Databases have extensive applications in the energy industry, encompassing data collection, storage, processing, and analysis. Graph databases, for example, have been applied in the power industry to uniquely describe physical equipment and facilitate data sharing, thereby driving the transformation and upgrading of the energy industry.
Furthermore, as information security becomes the top priority in data management, the security of databases has received unprecedented attention. To address the risks of data breaches and unauthorized access, the database industry continuously introduces innovative security mechanisms such as data encryption, access control, and audit tracking, ensuring the security of data during storage, transmission, and processing.
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