By using cloud-native databases that support online transaction processing, as well as offline batch processing and big data workloads, Alibaba had been able to achieve zero downtime in what has now become the world’s largest online shopping event.
As an example of the workloads that Alibaba’s database systems were grappling with this year, PolarDB, a relational database, set a new record with 140 million queries per second during peak time, a 60% increase from last year. In addition, AnalyticDB, the company’s self-developed cloud-native data warehouse, processed up to 7.7 trillion lines of real-time data, equaling 15 times the data contained in the UK web archive at the British Library.
The same database systems were also used by China Post to deal with over 100 million orders during the shopping event, with about 100,000 China Post users checking their parcels’ real-time status online.
“Many Fortune 500 firms are already using our Cloud DBaaS for mobile apps, backups and tests, and the most recent impressive performance of our proprietary solutions during the 11.11 global shopping festival is yet another strong endorsement on our capability.”
The high volume of database workloads did not require the use of more compute resources. Not only did Alibaba Cloud support one of the world’s largest container clusters, upscaling to as many as one million containers in an hour, it was able to reduce the amount of computing resources needed for every 10,000 transactions by 80% compared to four years ago.
“We were very proud to support 800 million consumers and 250,000 brands during the world’s largest shopping festival,” said Li Cheng, chief technology officer of Alibaba Group.
“From the robust digital infrastructure supporting zero downtime operation, to cloud-native offerings for developers’ efficiencies and consumer-facing applications for creating some of smoothest engagement experiences, Alibaba’s technologies have once again passed the toughest tests with flying colors.”
The following is another case of how STO Express smoothly handled the 618 shopping festival business peak by migrating its Oracle databases to PolarDB.
STO Express is a private express delivery company that started business operations early in China. In the past, traditional Internet of Everything (IoE) architecture used to be able to support its business operations. However, with the rapid development of the company's business, its original IT system encountered a bottleneck. Take the e-commerce promotion event as an example. In the past, STO Express had to expand Oracle hardware and databases several months in advance to be prepared for the event. However, after the promotion, the utilization of IT resources was very low, resulting in a poor return on investment (ROI).
At the end of 2019, STO Express decided to fully replace its IT infrastructure with Alibaba Cloud products, making it the first company in the express delivery industry to migrate all its products to the cloud. STO Express took the lead in migrating its core systems, such as the order platform and its "Baqiang" system, to the cloud. Since then, STO Express was able to handle nearly 30 million orders per day. Before this year's shopping festival major promotion, STO Express accelerated the pace of migrating its business systems such as those for managing scattered orders and package collection, to the cloud, and replaced Oracle databases with PolarDB cloud-native databases from Alibaba Cloud.
PolarDB's architecture separates storage and computing resources to achieve minute-level resilience. It can be quickly scaled out to support business soaring during peak hours at minimized costs. During this year's 618 shopping festival, PolarDB provided great support for STO Express by reducing IT costs by more than 50%.
Yang Henglian, the technical manager of STO Express' scattered order platform said: "STO Express has always attached great importance to the cost of its IT infrastructure. Today, the access burden per resource in PolarDB is several times higher than before the cloud migration, which is highly dependent on the PolarDB's cloud-native architecture and high-performance kernel. In addition, its parallel query function can easily complete multi-dimensional queries in the background of the scattered order platform. These facts prove that PolarDB is definitely the right choice for cloud logistics customers."
Li Feifei, the head of Alibaba Cloud Databases recently stated that after years of technological evolution, "Going O" has stepped in a large-scale crucial stage. This year, Alibaba Cloud will help 1,000 enterprises to "Go O", migrating 10,000 traditional data warehouses to the cloud.
ApsaraDB for PolarDB is a cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. ApsaraDB for PolarDB provides the performance and availability of traditional enterprise databases and the flexibility and cost-effectiveness of open-source databases.
ApsaraDB for PolarDB is designed for business-critical database applications that require fast performance, high concurrency, and automatic scaling. You can scale up to millions of queries per second and 100 TB per database cluster with 15 low latency read replicas. ApsaraDB for PolarDB is six times faster than standard MySQL databases, and delivers the security, reliability, and availability of traditional commercial databases at 1/10 the cost. ApsaraDB for PolarDB embodies the proven database technology and best practices honed over the last decade that supported hyper-scale events such as the Alibaba Double 11 Global Shopping Festival.
AnalyticDB for MySQL is a real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol and SQL:2003 syntax and can perform instant multidimensional analysis and business exploration for huge amounts of data.
This topic provides the test results of online transaction processing (OLTP) performance of PolarDB for MySQL 8.0.
This topic describes the results of this performance test on AnalyticDB for MySQL, MySQL, Presto, Apache Spark, and Apache Impala.
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