Alibaba Cloud Launches Enterprise-Level Cloud-Native Data Lake during 2020 Double 11
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On October 23, the 2020 Data Lake Summit was held in Beijing. Alibaba Cloud announced the launch of an enterprise-level cloud-native data lake solution. This solution provides data storage and analysis capabilities at the exabyte level. By doing this, Alibaba Cloud can realize comprehensive lake storage, lake acceleration, lake management, and lake computing, helping enterprises perform in-depth data mining and analysis, and gain insight into the data. Therefore, this data lake solution is more suitable for emerging industries with massive data scenarios, such as artificial intelligence (AI), Internet of Things (IoT), and autonomous driving.
Chen Qikun, Senior Director of Alibaba Cloud’s intelligent storage products, said, “The cloud-native enterprise-level data lake solution will be applied on a large scale during the Double 11 Global Shopping Festival for the first time this year. The solution will support Alibaba’s economy and millions of customers to fully access the cloud, unleashing the value of data to the greatest extent.”
The cloud-native enterprise-level data lake solution of Alibaba Cloud adopts the storage and computing separation architecture. This solution is based on the Alibaba Cloud Object Storage Service (OSS) and created in combination with the Alibaba Cloud Data Lake Analytics (DLA), Data Lake Formation (DLF), and E-MapReduce (EMR). This solution is compatible with a wide range of open-source engine ecosystems, meeting the needs of large-scale unified data storage. As such, the cloud-native enterprise-level data lake solution is more reliable, flexible, and secure.
The concept of a data lake is not new. Ten years ago at the Hadoop Summit in New York, a data lake was proposed and defined, “to pour what you have on tape into a lake of data and then start to explore the data.” With the development of big data, cloud storage, and cloud computing, today, the concept of a data lake is mature and has been widely brought into practice in various enterprises.
Unlike traditional big data solutions, the cloud-native data lake solution is based on the next-generation data lake architecture. By adopting this solution, customers can directly access the business production center, including the raw data and log data in the business system. Also, data can be directly stored in the data lake through the Internet without intermediate processing, improving business efficiency by 100%, and driving the shift of enterprise IT systems from a cost center to an innovation center.
We can use a well-known multiplayer online gaming company in China as an example. Based on the Alibaba Cloud data lake solution, this company delivered its global data to OSS in real-time using Log Service (SLS). The company took advantage of the massive elastic capabilities of OSS to separate hot and cold data as well as the EMR and DLA to build a big data architecture for separating storage and computing. As such, the company can perform real-time channel statistics and real-time analysis of the best process for tens of millions of active gamers daily. These refined operations have helped the company increase user retention by 30%. Currently, thousands of enterprises have built their data lakes on Alibaba Cloud.
Li Feifei, Vice President of Alibaba Group and the Head of Alibaba Cloud’s Intelligent Database Product Division, believed that the integration of databases and big data is accelerating the large-scale implementation of data lakes. The cloud-native data lake allows enterprises to mine the value of data in a more flexible, agile, efficient, and easier way, without needing to manage computing resources. The data lake also empowers enterprises to regenerate and innovate quickly, making data insights a core competency of enterprises.
According to Jia Yangqing, Vice President of Alibaba Group and the Head of the Alibaba Cloud’s Intelligent Computing Platform Division, the solution that enterprises want is based on the Alibaba Cloud data lake OSS and data warehouse MaxCompute without data transmission. The data can be flowed intelligently and computed through multiple platforms. The solution will ensure the continuity and timeliness of the data services of enterprises due to its combination with the flexibility of the data lake and the growth of the data warehouse.
“In the digital economy era, if we think of big data like oil and computing power as an engine, the cloud-native enterprise-level data lake will be a solution that can integrate both of them. In the near future, a data lake will become a standard for enterprise innovations, helping enterprises achieve intelligent and digital transformation in an all-round way,” said Chen Qikun.