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Big Data and Hadoop are the two most familiar terms currently being used. Both are inter-related in a way that without the use of Hadoop, Big Data cannot be processed. In this article, I will give you a brief insight into Big Data vs Hadoop.
Let’s get started!
Big Data is a term used for a collection of data sets that are large and complex, which is difficult to store and process using available database management tools or traditional data processing applications. The challenge includes capturing, curating, storing, searching, sharing, transferring, analyzing and visualization of this data.
The three different formats of big data are:
Structured: Organised data format with a fixed schema. Ex: RDBMS
Unstructured: Unorganized data with an unknown schema. Ex: Audio, video files, etc.
So, now that you know what is big data let’s now understand what is big data analytics.
Basically, Big Data Analytics is largely used by companies to facilitate their growth and development. This majorly involves applying various data mining algorithms on the given set of data, which will then aid them in better decision making. There are multiple tools for processing Big Data such as Hadoop, Pig, Hive, Cassandra, Spark, Kafka, etc. depending upon the requirement of the organization.
Hadoop is an open-source software framework used for storing and processing Big Data in a distributed manner on large clusters of commodity hardware. Hadoop is licensed under the Apache v2 license. Hadoop was developed, based on the paper written by Google on the MapReduce system and it applies concepts of functional programming. Hadoop is written in the Java programming language and ranks among the highest-level Apache projects. If you wish to know more about Hadoop, then kindly check out Hadoop Tutorial.
Now that you know the basics of Big Data and Hadoop, let’s move further and understand the difference between Big Data and Hadoop
|Big Data refers to a large volume of both structured and unstructured data.||Hadoop is a framework to handle and process this large volume of Big data|
|Big Data has no significance until it is processed and utilized to generate revenue.||It is a tool that makes big data more meaningful by processing the data.|
|It is very difficult to store big data because it comes in structured and unstructured form.||Apache Hadoop HDFS is capable of storing big data.|
|When it comes to accessing the big data, it is very difficult.||Hadoop framework lets you access and process the data very fast when compared to other tools.|
So, that was all about the major comparison between Big Data and Hadoop. If you wish to gain more insights on Big Data and Hadoop and what are the features of the framework, you can check out this Big DataTutorial.
This blog brings us to the end of this article on Big Data vs Hadoop. I hope this blog was informative and added value to your knowledge.
Now that you have understood Hadoop and its features, check out the Hadoop Training by Edureka, a trusted online learning company with a network of more than 250,000 satisfied learners spread across the globe. The Edureka Big Data Hadoop Certification Training course helps learners become expert in HDFS, Yarn, MapReduce, Pig, Hive, HBase, Oozie, Flume and Sqoop using real-time use cases on Retail, Social Media, Aviation, Tourism, Finance domain.
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