How Nosql Works

NoSQL: How developers respond to big data release time: 2012.04.16 14:15 Source: Developer Author: Developer Current Large data is the hottest trend in the field of High-performance computing. Large data processing is characterized by: we need real-time collection, analysis, transmission of massive information, data set to PB or even ZB (1 million PB) as a unit, the large number of developers to bring new challenges, talked about large data, on ...

This is my second time for the new project in-depth research NoSQL, but also the second decision to give up NoSQL. 　　Like the conclusion I made last time about why I chose to use nosql so hard, we finally decided to give up NoSQL and use a traditional relational database. I've come up with a lot of comments from the last post to evaluate NoSQL-the core of the solution is "depending on your needs." But despite the need for clarity, it still takes time to research and find out whether a particular NoSQL engine is exactly what you need. There are so many ways that you can't ...

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 ...

There are many methods for processing and analyzing large data in the new methods of data processing and analysis, but most of them have some common characteristics. 　　That is, they use the advantages of hardware, using extended, parallel processing technology, the use of non-relational data storage to deal with unstructured and semi-structured data, and the use of advanced analysis and data visualization technology for large data to convey insights to end users. 　　Wikibon has identified three large data methods that will change the business analysis and data management markets. Hadoop Hadoop is a massive distribution of processing, storing, and analyzing ...

Large data processing technology is changing the current operating mode of the computer. We've got a lot of revenue from that because it's the big data processing technology that brings us search engine Google. 　　But the story is just beginning, and for several reasons, we say that large data processing technology is changing the world: * It can handle almost every type of data, whether it's microblogging, articles, emails, documents, audio, video, or other forms of data. 　　* It works very fast: practically in real time. * It's universal: because it's ...

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

Will large data policies fail? It's time to discuss the problem. Enterprises have just mastered how to integrate ERP (Enterprise resource planning) and other business applications to eliminate the obstacles to efficiency in the business process. Service-oriented architecture, software-services, cloud computing and other modern solutions have played a role in helping enterprises achieve large-scale application integration. But today, organizations are facing a new set of challenges in a large number of data environments. More clearly, it is not a data stream. It is made up of a number of independent data streams, separating the data from each other or just like the previous enterprise application ...

Will large data policies fail? It's time to discuss the problem. Enterprises have just mastered how to integrate ERP (Enterprise resource planning) and other business applications to eliminate the obstacles to efficiency in the business process. Service-oriented architecture, software-services, cloud computing and other modern solutions have played a role in helping enterprises achieve large-scale application integration. But today, organizations are facing a new set of challenges in a large number of data environments. More clearly, it is not a data stream. It is made up of a number of independent data streams, separating the data from each other or just like the previous enterprise application ...