Mongodb Scalability Limits

MongoDB company formerly known as 10gen, founded in 2007, in 2013 received a sum of 231 million U.S. dollars in financing, the company's market value has been increased to 1 billion U.S. dollar level, this height is well-known open source company Red Hat (founded in 1993) 20 's struggle results. High-performance, easy to expand has been the foothold of the MongoDB, while the specification of documents and interfaces to make it more popular with users, this point from the analysis of the results of Db-engines's score is not difficult to see-just 1 years, MongoDB finished the 7th ...

http://www.aliyun.com/zixun/aggregation/13461.html"> MongoDB, formerly known as 10gen, was founded in 2007 and after receiving a total of $ 231 million in 2013, the company's market capitalization has risen to 10 Billion dollar level, which is the result of 20 years of Red Hat, a well-known open-source company founded in 1993. High performance and easy scalability have been the foundation of MongoDB and meanwhile standardized documents ...

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 ...

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 appearance of MapReduce is to break through the limitations of the database. Tools such as Giraph, Hama and Impala are designed to break through the limits of MapReduce. 　　While the operation of the above scenarios is based on Hadoop, graphics, documents, columns, and other NoSQL databases are also an integral part of large data. 　　Which large data tool meets your needs? The problem is really not easy to answer in the context of the rapid growth in the number of solutions available today. Apache Hado ...

Since March 20, 2013 Docker appeared in front of developers, less than two years now. "Docker has transformed from a great idea into a great technology, and from a great technology to a great ecosystem, and even from a great ecosystem to a great movement." "I remember at the Docker summit in 2013, developers were still talking about Docker, and at the 2014 Amsterdam Summit, participants were already sharing its case." However, Docker's business ...

With the development of the Internet, mobile Internet and IoT, no one can deny that we have actually ushered in a massive data era, data research company IDC expects 2011 total data will reach 1.8 trillion GB, the analysis of these massive data has become a very important and urgent demand. As an Internet data analysis company, we are "revolt" in the field of analysis of massive data. Over the years, with stringent business requirements and data pressures, we've tried almost every possible big data analysis method, and finally landed on the Hadoop platform ...

The industry has divergent views on the concept of large data. One of the most notable is the definition of the authoritative research institute Gartner: Large data is the ability to gather, manage, and process data for its users over an acceptable period of time, beyond the common hardware environment and software tools. Large data is not a simple data capacity, data speed, complexity and diversity are the key characteristics of large data. Big data often comes from new data sources, where unstructured data is the absolute mainstay. Unstructured data refers to those data that are not convenient to use in two-dimensional logical tables of the database, including all forms of office ...

How fast is the tide of big data? IDC estimated that the amount of data produced worldwide in 2006 was 0.18ZB (1zb=100), and this year the number has been upgraded to a magnitude of 1.8ZB, which corresponds to almost everyone in the world with more than 100 GB of hard drives. This growth is still accelerating and is expected to reach nearly 8ZB by 2015. For now, large data processing is facing three bottlenecks-large capacity, multiple format and speed, and the corresponding solution is proposed, which is extensibility, openness and next-generation storage technology. Capacity-high expansion ...

The industry has divergent views on the concept of large data. One of the most notable is the definition of the authoritative research institute Gartner: Large data is the ability to gather, manage, and process data for its users over an acceptable period of time, beyond the common hardware environment and software tools. Large data is not a simple data capacity, data speed, complexity and diversity are the key characteristics of large data. Big data often comes from new data sources, where unstructured data is the absolute mainstay. Unstructured data refers to those data that are not convenient to use in two-dimensional logical tables of the database, including all forms of office ...