Cloud And Distributed Databases 2017

As early as 2010 and 2011, the prediction of the glorious future of cloud computing became the headline news. Analysts predict that the arrival of cloud computing is the best technological development since the invention of the computer.

In the past two years, the overall penetration rate of cloud computing has been continuously improved, and the turning point of the industry has arrived.

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

After more than eight years of practice, from Taobao's collection business to today to support all of Alipay's core business, and in the annual "Double Eleven Singles Day" continue to create a world record for the transaction database peak processing capacity.

Follow the latest trends of E-commerce in China by reading articles about Double Eleven Singles Day.

In 2017, the double eleven refreshed the record again. The transaction created a peak of 325,000 pens/second and a peak payment of 256,000 pens/second. Such transactions and payment records will form a real-time order feed data stream, which will be imported into the active service system of the data operation platform.

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

Today, some of the most successful companies gain a strong business advantage by capturing, analyzing, and leveraging a large variety of "big data" that is fast moving. This article describes three usage models that can help you implement a flexible, efficient, large data infrastructure to gain a competitive advantage in your business. This article also describes Intel's many innovations in chips, systems, and software to help you deploy these and other large data solutions with optimal performance, cost, and energy efficiency. Big Data opportunities People often compare big data to tsunamis. Currently, the global 5 billion mobile phone users and nearly 1 billion of Facebo ...

2014 Zhongguancun Large Data day on December 11, 2014 in Zhongguancun, the General Assembly to "aggregate data assets, promote industrial innovation" as the theme, to explore data asset management and transformation, large data depth technology and industry data application innovation and ecological system construction and so on key issues. The Conference also carries on the question of the demand and practice of the departments in charge of the government, the finance, the operators and so on to realize the path of transformation and industry innovation through the management and operation of data assets. In the afternoon of the government @big Data Forum, heavy ...

Big data will become the cloud of the year. This is the inevitable result: over time, the enterprise produces more and more data sets, including customer purchase preference trends, site visits and habits, customer review data, etc. so how can you put so much data into a comprehensive form? Traditional business Intelligence (BI) tools (relational databases and desktop math packages) are a bit out of the way to deal with such a large amount of data in a business. Of course, the data analysis industry also has development tools and frameworks to support data researchers and analysts in mining large datasets, and can underwrite ...