Large Data processing tool: Hadoop has five advantages

Now, if you haven't heard of Hadoop, you must be behind the time. As a new Open-source project, Hadoop provides a new way to store and processor data. Large http://www.aliyun.com/zixun/aggregation/3518.html "> Internet companies, such as Google and Facebook, use Hadoop to store and manage their huge datasets. Hadoop has also proven its five advantages through its application in these areas:

High scalability

Hadoop is a highly scalable storage platform because it can store and distribute inexpensive server data clusters across hundreds of parallel operations. Unlike traditional relational database systems that cannot be extended to handle large amounts of data, Hadoop is an application that can provide an enterprise with hundreds of terabytes of data nodes running on it.

Cost effectiveness

Hadoop also provides an extremely cost-effective storage solution for enterprise users. The problem of the traditional relational database management system is that he does not meet the large data processor and can not meet the cost benefit of the enterprise. Many companies used to assume that the best value for the data, and then set the classification based on these valuable data, and if all the data were saved, the cost would be too high. Although this method can be implemented in a short time, but as the volume of data increases, this approach does not solve the problem very well.

Hadoop's architecture is not painful, it is designed as an outward-expanding architecture that can economically store all the company's data for later use, the cost savings are very staggering, Hadoop provides hundreds of TB of storage and computing power, not thousands of dollars can solve the problem.

Flexibility is better

Hadoop makes it easy for businesses to access new data sources, and can analyze different types of data to generate value from that data, which means that businesses can leverage Hadoop's flexibility to gain valuable business value from data sources such as social media, e-mail, or click traffic.

In addition, Hadoop uses a wide range of applications, such as logarithmic processing, referral systems, data warehousing, campaign analysis, and fraud detection.

Fast

Hadoop processing Faster

Hadoop has a unique way of storing data, and the tools used for data processing are usually on the same server as the database, resulting in faster processor data, and if you're working on a lot of unstructured data, Hadoop can effectively process terabytes of data in minutes, Instead of the PB-level data as it was before, it was measured in hours.

Fault tolerance

One of the key advantages of using Hadoop is his ability to fault tolerance. When the data is sent to a separate borrowing point, the data is also replicated to other nodes in the cluster, which means that there is another copy available in the event of a failure.

Summary: Hadoop has an advantage over relational database management systems when it comes to dealing with large datasets and security and cost-effectiveness. It applies to enterprises with continuous growth of unstructured data of any size, which will help enterprises to continuously discover business value.