Cloud Native Database 2.0: One-stop full-link data management and service

Introduction to Cloud Developers Conference on May 29, Alibaba Cloud Database announced the new brand concept and open source cloud native database capabilities of "Cloud Native Database 2.0: One-stop Full Link Data Management and Services". The customer scenario perspective puts forward the concept of a one-stop online data management platform.

At present, Alibaba Cloud has the most powerful and abundant cloud database product family in China, covering four major sections: relational databases, non-relational databases, data warehouses, and database ecological tools. It can provide enterprise data production and integration, real-time processing, analysis and discovery , Development and management provide full link life cycle services.

截屏2021-05-31 下午12.13.09.png

Data production and integration

The production and integration of data is the first life cycle of data. Just like a newborn baby, when data comes to this world, it must first undergo collection, then storage and processing. Tools such as Alibaba Cloud Data Transmission DTS, Data Management DMS, and Database Backup DBS constitute the basic capabilities of data production and integration. Through the unified management of 30+ data sources in the hybrid cloud, various solutions such as data collection, real-time transmission of heterogeneous data, multiple activities in different places, cross-cloud backup or backup to the cloud, etc. are realized. Data can be improved through the database DevOps capability provided by DMS Safety and R&D collaboration efficiency.

Real-time data processing

After completing the production and integration of data, it will naturally come to the real-time processing of data. How to ensure that the application is always online and the data is never lost in the online transaction scenario must be the most concerned issue for everyone. Here, Alibaba Cloud Database provides different options.

Alibaba Cloud RDS is the largest and most stable cloud database in China, supporting MySQL, PG, SQL Server and other engines, supporting the rapid development of Alibaba economy for more than ten years, providing 99.99% high availability and RPO=0 enterprise-level capabilities. In the cloud native database 2.0 era, the biggest feature of Alibaba Cloud RDS is to provide enterprise-level database autonomy. Through AI and machine learning technology, an autonomous driving database platform is built to support automatic problem repair and automatic tuning.

Alibaba Cloud's self-developed cloud-native relational database PolarDB adopts the separation of storage and calculation, and the integration of software and hardware. It not only has the low-cost advantage of distributed design, but also has centralized ease of use, which can meet the needs of large-scale application scenarios. The computing power can be expanded to more than 1000 cores, the storage capacity can be up to 100TB, and the cluster version single database can be expanded to 16 nodes at most, and the performance is 6 times higher than MySQL. PolarDB series products have been supporting Tmall Double 11 stably for many years, and the processing peak is up to a record 140 million times per second.

Data analysis and discovery

After accumulating a large amount of transaction data, how to find information in the data to create greater value for the business comes to the life cycle stage of data analysis and discovery.

The cloud native data warehouse AnalyticDB, based on the storage and computing separation architecture, is integrated offline. A piece of stored data meets multiple computing capabilities such as interactive analysis, real-time update, high concurrency check and offline computing, and solves the complexity of traditional analysis system architecture. For the problem of high construction threshold and high cost, 1TB can be as low as 114 yuan/month. Cloud native database 2.0 can also discover and analyze offline data through data lake technology to build a lake-warehouse integrated solution.

Data development and management

Finally, data development and management. Through the data management service DMS, companies can manage online data assets in a unified manner, including metadata management, security desensitization, and blood relationship analysis, to achieve low-threshold on-demand warehouse building and agile analysis capabilities.

The biggest change brought about by the one-stop online data management platform is that enterprises can manage large amounts of data in the form of databases. DMS uniformly manages the database and data warehouse, allowing data to flow freely. Different from traditional data integration, DMS can not perceive the link in the source database DDL or expansion and contraction operation and maintenance changes, and the built-in ETL capability shortens the data link, and at the same time, it can directly query the source database table through cross-database query. Participate in the calculation as the ODS layer of the data warehouse, eliminating the problem of physical data relocation, and truly achieving on-demand warehouse building and agile analysis. DMS also supports flexible task scheduling, data development, and report display. With the accumulation of data, DMS can periodically archive data to the cloud-native multi-mode database Lindorm or OSS, use data lake analysis to mine the value of DBS backup data, and perform full life cycle management of the data to give full play to the value of the data.

One-stop online data management platform, through the unified management of online data assets, full-link security and blood relationship management, and building an integrated warehouse and offline storage and computing capabilities, will greatly reduce the threshold for enterprise data processing and analysis. Help enterprises to better utilize the value of data and assist enterprises in their digital transformation.


Cloud Database Leader Li Feifei said: "For cloud native database 2.0, we want to move from atomic product differentiation to one-stop full-link data management and service , so that developers and customers can discover value from data. Let data flow seamlessly, this is our philosophy and our mission."

Copyright statement: content of this article is contributed spontaneously by Alibaba Cloud real-name registered users. The copyright belongs to the original author. The Alibaba Cloud Developer Community does not own its copyright and does not assume corresponding legal responsibilities. For specific rules, please refer to the "Alibaba Cloud Developer Community User Service Agreement" and the "Alibaba Cloud Developer Community Intellectual Property Protection Guidelines". If you find suspected plagiarism in this community, fill in the infringement complaint form to report it. Once verified, the community will immediately delete the suspected infringing content.


3.1k 声望
6.2k 粉丝
0 条评论

阿里云开发者阅读 550

http 和 https 的通信过程及区别
🎈 两者的区别端口: http 端口号是80, https 端口号是443传输协议: http 是超文本传输协议,属于明文传输; https 是安全的超文本传输协议,是经过 SSL 加密后的传输协议安全性: https 使用了 TLS/SSL 加密,...

tiny极客2阅读 2.8k评论 2

DeepMind 发布强化学习通用算法 DreamerV3,AI 成精自学捡钻石
内容一览:强化学习是多学科领域的交叉产物,其本质是实现自动决策且可做连续决策。本文将介绍 DeepMind 最新研发成果:扩大强化学习应用范围的通用算法 DreamerV3。关键词:强化学习 DeepMind 通用算法

超神经HyperAI1阅读 896

JWT 登录认证
🎈 Token 认证流程作为目前最流行的跨域认证解决方案,JWT(JSON Web Token) 深受开发者的喜爱,主要流程如下:客户端发送账号和密码请求登录服务端收到请求,验证账号密码是否通过验证成功后,服务端会生成唯一...

tiny极客2阅读 936评论 1


京东云开发者3阅读 421

6 大经典机器学习数据集,3w+ 用户票选得出,建议收藏
内容一览:本期汇总了超神经下载排名众多的 6 个数据集,涵盖图像识别、机器翻译、遥感影像等领域。这些数据集质量高、数据量大,经历人气认证值得收藏码住。关键词:数据集 机器翻译 机器视觉

超神经HyperAI1阅读 1.1k

90 后学霸博士 8 年进击战,用机器学习为化学工程研究叠 BUFF
本文首发自公众号:HyperAI 超神经 内容一览:ScienceAI 作为近两年的技术热点,引起了业界广泛关注和讨论。本文将围绕 ScienceAdvances 的一篇论文,介绍如何利用机器学习,对燃煤电厂的胺排放量进行预测。 关键...

超神经HyperAI1阅读 886


3.1k 声望
6.2k 粉丝