Nosql Speed Comparison

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Discussion on NoSQL database

With the rise of internet web2.0 websites, the relational database has become a very hot new field, the development of the non relational database products is very rapid.   But the traditional relational database in dealing with web2.0 website, especially the super large-scale and high concurrent SNS type web2.0 pure dynamic website already appeared to be powerless, has exposed many insurmountable problems, for example: 1, high configured--to the database higher concurrent reads and writes the demand WEB2.0 website to be based on user personalized information to generate real-time dynamic ...

Database research in cloud computing era

Introduction with the advent of the cloud computing era, various types of Internet applications are emerging, the relevant data model, distributed architecture, data storage and other database related technical indicators also put forward new requirements. Although the traditional relational database has occupied the unshakable position in the data storage, but because of its inherent limitation, has been unable to satisfy the cloud computing age to the data expansion, reads and writes the speed, the support capacity as well as the construction and the operation cost request. The era of cloud computing has put forward a new demand for database technology, which is mainly manifested in the following aspects. Mass data processing: to ...

Comparison of 3 well-known cloud manufacturers under hat-trick

September 23, virtualization technology for the Linux kernel Xen was given a hat-trick with 3 security vulnerabilities. Xen vulnerabilities can be jumped out of the virtual host environment (ultra vires), or read other user data, control the hypervisor itself (host). A remote attacker could exploit a vulnerability that could cause the host system to crash and deny service to legitimate users. Xen Vulnerabilities and impact range is not small, such as Amazon AWS Large-scale restart server-the entire repair cycle lasted 5 days (from September 25 7 o'clock in the afternoon to September 30 5 o'clock in the afternoon), impact ...

Using HADOOP-RDMA to speed up large data processing

China's most influential and largest large data-gathering event--2013 China's Big Data Technology conference (DA data Marvell CONFERENCE,BDTC) was held in Beijing in December 2013 5-6th. Dozens of leading companies, nearly 70 lectures, not only covers the Hadoop ecosystem and flow calculation, real-time computing and NoSQL, Newsql and other technical direction, but also on the Internet, finance, telecommunications, transportation, medical and other innovative cases, large data resources laws and regulations, large data commercial use policy ...

The future of mass storage--memory cloud

The fastest way to store a computer system is the ram traditionally used primarily as memory. As the access performance of the hard drive has deteriorated over the years, and the cost of RAM has been decreasing, many researchers have been exploring how to replace the hard disk with memory in recent years. As early as the 1980, David DeWitt and Garcia-molina and so on published a main memory database paper. Steven Robbins's article points out that the Turing Prize winner, Jim Gray, is more explicit about the idea that "memory will be a hard drive and the hard drive will become a tape."

The evolution of cloud storage and big data

There are two main ways to store data: Database and filesystem, and the object-oriented storage are developed behind, but the overall thing is to store both structured and unstructured data. DB is initially serviced for structured data storage and sharing. FileSystem storage and sharing is large files, unstructured data, such as pictures, documents, audio and video. With the increase in data volume, stand-alone storage can not meet the needs of structured and unstructured data, then in the era of cloud computing, there is a distributed ...

The era of cloud computing, the solution of distributed storage and distributed database

There are two main ways to store data: Database and filesystem, and the object-oriented storage are developed behind, but the overall thing is to store both structured and unstructured data. DB is initially serviced for structured data storage and sharing. FileSystem storage and sharing is large files, unstructured data, such as pictures, documents, audio and video. With the increase in data volume, stand-alone storage can not meet the needs of structured and unstructured data, then in the era of cloud computing, there is a distributed ...

The evolution of cloud storage and big data

There are two main ways to store data: Database and filesystem, and the object-oriented storage are developed behind, but the overall thing is to store both structured and unstructured data. DB is initially serviced for structured data storage and sharing. FileSystem storage and sharing is large files, unstructured data, such as pictures, documents, audio and video. With the increase in data volume, stand-alone storage can not meet the needs of structured and unstructured data, then in the era of cloud computing, there is a distributed ...

The contention of time series data processing: MongoDB vs. Cassandra

Http://www.aliyun.com/zixun/aggregation/13461.html ">mongodb and Cassandra are the two most popular NoSQL databases, MongoDB is the NoSQL field is worthy of the popularity of the king, while the Cassandra is the perennial occupation of the column storage field chief, compared with the hbase of concern for many reasons have been second. Recently Mydrive soulutions operation and Frame ...

Hadoop Serialization System

This article is my second time reading Hadoop 0.20.2 notes, encountered many problems in the reading process, and ultimately through a variety of ways to solve most of the.   Hadoop the whole system is well designed, the source code is worth learning distributed students read, will be all notes one by one post, hope to facilitate reading Hadoop source code, less detours. 1 serialization core Technology The objectwritable in 0.20.2 version Hadoop supports the following types of data format serialization: Data type examples say ...

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