Recently, a remarkable event has occurred in the global database market. According to Gartner data, we found that Amazon Cloud Technology, as a pure cloud vendor, won the title of global database leader in 2022, accounting for 25.3% of the global market.
The development direction of cloud-native database: deep integration with data analysis and AI services
The road to innovation of cloud-native databases has just begun, and it is far from the end. For example, to build databases for different business scenarios, this "dedicated database" model can greatly improve the performance and efficiency of the database, helping customers better meet business needs; based on Serverless Database technology to achieve extreme flexibility. In the future, cloud-native databases may become more serverless and support more flexible billing models, such as billing by request, billing by data volume, etc. Global databases are an important solution for cloud-native databases to support global businesses of enterprises. The database can deploy database instances in multiple data centers around the world, providing functions such as data replication, load balancing, and failover to achieve global data consistency and business continuity.
In addition to the above advantages, it is particularly worth noting the deep integration of cloud-native databases with big data, AI, and the entire cloud computing system, which will bring huge impetus to the release of enterprise data value.
Data has become the fifth production factor after land, labor, capital, and technology. How to release the value of data elements through applications has become a question that the entire data industry needs to answer. As the foundation of the entire data intelligence building, the cloud-native database will better empower data applications by integrating the database with upper-level big data and AI services, which will be an important development direction of the cloud-native database.
Taking Amazon Cloud Technology as an example, it builds an end-to-end data strategy covering data storage, query, data analysis, machine learning, business intelligence, cataloging and governance based on cloud-native databases.
As the world's leading cloud provider, Amazon Cloud Technology provides a series of powerful cloud-native database, big data and AI services. These services are tightly integrated to provide a one-stop data platform that supports various complex data applications. For example, Amazon Redshift provides a fully managed PB-level data warehouse service, allowing users to perform large-scale data analysis on the cloud; Amazon S3 is tightly integrated with services such as Redshift, EMR, and Athena, providing a powerful solution for big data processing and analysis. Support; Amazon EMR supports various big data processing modes such as batch processing, interactive query, machine learning, and stream processing, and integrates services such as S3, Redshift, and DynamoDB. Users can directly process data in these services in EMR; SageMaker is A fully managed machine learning service that integrates Amazon Cloud Technology's big data and database services. Users can directly process data in these services, simplifying the machine learning process; QuickSight, as a business intelligence service, integrates Amazon Cloud Technology's database And big data services, users can directly access and analyze the data in these services in QuickSight, and then perform visual analysis on the data.
In a cloud environment, the integration of databases, big data, and AI services is particularly important. They do not exist in isolation, but perform their duties in the data life cycle and cooperate with each other to provide a full-process solution from data collection, storage, processing, analysis to final application.
Cloud-native database, in addition to its significant advantages in terms of scalability, elasticity, reliability and other technical characteristics, more importantly, it can quickly integrate other important elements in cloud services to form a complete ecosystem of data processing and analysis . In this ecosystem, services such as databases, big data, and AI complement each other to form a powerful "combat cluster".
In this case, companies that provide comprehensive, integrated cloud services are clearly more competitive. They can provide customers with one-stop solutions, reduce customers' troubles in technology selection and integration, and enable customers to focus more on their business, which is difficult for many single database companies to replicate.
Cloud-native databases can seamlessly interact with other services on the cloud platform (such as big data processing tools, AI and machine learning services, etc.) through APIs and service calls. This integration capability makes it easier for developers to build, deploy and scale complex applications. For example, data can be read from cloud-native databases, then processed through big data services, and finally model training and predictions through AI services. The entire process does not require data migration, which not only improves efficiency, but also reduces the risk of data loss or leakage. However, due to the lack of corresponding cloud services such as big data and AI, traditional single database companies often need to integrate through third-party services, which will involve issues such as data transmission, security, performance optimization, and compatibility. The cost will be relatively high.
In addition, cloud service providers usually have a rich service system, such as storage services, computing services, network services, security services, etc. These services can be deeply integrated with cloud-native databases to form a complete solution to meet various needs of users. As for single database companies, they often can only provide database services and cannot provide comprehensive solutions, which limits their flexibility and comprehensiveness in meeting user needs.
To sum up, cloud-native database has become the direction of database development, which stems from its advantage of cloud computing and its ability to process large-scale, diverse, and real-time data. Cloud-native databases not only meet traditional storage and query requirements, but also become an important platform for data-driven decision-making and intelligent applications following the trend of big data and AI integration.
In this context, comprehensive cloud vendors that can provide cloud-native databases, such as Amazon Cloud Technology, have been promoting the development and provision of cloud-native databases through their advantages in cloud service integration, big data processing, and AI technology, as well as a rich ecosystem. Significant advantages have been demonstrated in integrated services. Comprehensive cloud vendors such as Amazon Cloud Technology will continue to lead the development of databases, promote the integration of cloud-native databases with big data and AI, promote digital transformation and digital economy construction, release the value of data as a new factor of production, and further promote the digitalization of society.