The difference between Big Data and Hadoop is an open discussion and quite distinctive and fundamental. Big Data is a type of asset and quite complex while Hadoop is an open source program that accomplishes define goals and tasks.
Fundamentally Big Data is a large set of data that businesses and other applications confine together for a specific goal and objective. It may include many different kinds of data in many different formats. For example, Business can collaborate into a big data by collecting the thousands of piece of data on purchase in currency formats or social security number or purchased products model numbers, sales details and number or inventory of the stocks. It contains the massive heaps of information, can be called big data. As a mandatory rule, the data remains raw and unsorted and is filtered through various tools and software handlers.
On the other hand, Hadoop is one of the tools that is used to handle the big data. With the help of Hadoop and the other software, the major work is to interpret or analyze the results of the big data searches with the help of algorithms and methods. This open source program is covered through Apache Licenses and is maintained by the global community of the users worldwide. The significant components are MapReduce which is a set of instructions along with the Hadoop distributed file systems. MapReduce can map an extensive collection of data, and the perform the reduction on the content yielded through the result. The reduction is achieved through the filters on the raw data whereas the HDFS system acts to segregate the data across several networks and propagate as required. Many of the database administrators and developers use Hadoop to deal with the big data in several ways.
