Alibaba Cloud Ranks Third Globally By Gartner’s Database Management Services Revenue
Alibaba Cloud, the data intelligence backbone of Alibaba Group, generated the third largest cloud database management system (DBMS) revenue among global players, according to a recent report entitled Gartner, The Future of the DBMS Market Is Cloud, Donald Feinberg et al., 21 June 2019.
According to this report conducted by global analyst firm Gartner, Alibaba Cloud’s DBMS revenue increased by 116% year-on-year in 2018. Cloud DBMS revenue of the other two market leaders Amazon and Microsoft grew by 75% and 134% respectively.
“Cloud-native databases like Alibaba Cloud’s PolarDB will be the future of database innovations,” said Lancelot Guo, Vice President of Alibaba Group and General Manager of Strategy and Marketing at Alibaba Cloud. “As enterprises increasingly migrate their on-premises databases to the cloud, cloud-native DBMS providers like Alibaba Cloud will be well positioned to benefit from the exponential growth of the DBMS market. We are a strong and competitive services provider for public services, as well as for the retail, finance and manufacturing sectors.”
Alibaba Cloud is a pioneer in open-source DBMS and an advocate of distributed DBMS. The company boasts a full suite of database products, ranging from relational, NoSQL and analytic database services to database migration tools.
Among these products, PolarDB is a new generation of cloud-native database that combines performance with compatibility and availability of traditional enterprise databases at a much lower cost. It can scale up to 100TB in storage, 88 vCPUs and 710GB of memory which helps customers effectively manage big data development. It allows customers to pay for usage by the minute, enabling them to handle peak business traffic while minimizing cost.
Alibaba Cloud has successfully migrated some 400,000 database instances to the cloud. Its powerful database services have endured the toughest pressure test of Alibaba Group’s 11.11 Global Shopping Festival, which involved managing peak traffic volumes of approximately 100 times the daily average.