Database Scalability Techniques

The scalability of the system is the main reason for promoting the development of NoSQL movement, including distributed system coordination, failover, resource management and many other features. That makes NoSQL sound like a big basket that can be stuffed with anything. Although the NoSQL movement does not bring fundamental technological changes to distributed data processing, it still leads to extensive research and practice on protocols and algorithms. It is through these attempts to gradually summarize some effective database construction methods. In this article, I will focus on the distributed features of the NoSQL database ...

The scalability of the system is the main reason for promoting the development of NoSQL movement, including distributed system coordination, failover, resource management and many other features. That makes NoSQL sound like a big basket that can be stuffed with anything. Although the NoSQL movement does not bring fundamental technological changes to distributed data processing, it still leads to extensive research and practice on protocols and algorithms. It is through these attempts to gradually summarize some effective database construction methods. In this article, I will focus on the NoSQL database distributed special ...

Today's world is a large data age of the information world, our life, whether life, work, learning are inseparable from the support of information systems. The database is the place behind the information system for saving and processing the final result. 　　Therefore, the database system becomes particularly important, which means that if the database is facing problems, it means that the entire application system will also face challenges, resulting in serious losses and consequences. Now the word "Big Data age" has become very popular, although it is unclear how the concept landed. But what is certain is that as the internet of things 、...

Enterprises in the process of information often use a number of systems such as enterprise resource planning (Enterprise Resource planing,erp), Customer relationship management (customers relationship MANAGEMENT,CRM), etc. The database data used by these systems are independent, which increases the difficulty of managing costs and maintenance. Private cloud and database consolidation can reduce system costs and complexity, improve flexibility and quality of service; Private cloud can be implemented for servers, storage, applications, or IT services ...

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 ...

"IT168 Database Conference Report" April 2013 18-20th, the Third China Database Technology Congress (DTCC 2013) kicked off at four points by Sheraton Beijing Hotel. During the three-day meeting, the Conference will explore a wide range of technology areas such as large data applications, data architecture, data management (data governance), traditional database software, and will invite a group of top technical experts to share. On the basis of retaining the traditional theme of database software application practice, this session will lead to large data, data structure, data management and analysis, business intelligence ...

In the previous article, we have scanned the recognition and attention of large data based on China's different regions and industries, and seen the acceptance and development potential of the x86 architecture as a large data base platform, in combination with the ZDNet launch of China's large data recognition and application market research. This article will be based on the previous article, combined with database application and related technologies to interpret the research report, and summed up several major findings and conclusions. The data of large data analysis and storage require vigorous research, in addition to the recognition that large data has large capacity, production ...

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, ...

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, ...

I think the data Warehouse can help the enterprise to deal with the data problem in three ways: first, in an enterprise Data warehouse, you divide your data according to the subject area, which is often more stable. 　　Organizations that want to understand the "big data" concept need to make a choice between the traditional data warehouse concept and the existing Data Warehouse architecture, or the increasingly popular open source Hadoop distributed processing platform, or the combination of the two. Those who want to move from simple BI reports to deep data mining and predictive analytics ...