Key Difference – Big Data vs Hadoop
Data is collected widely all over the world. This large amount of data is called Big data or Big Data and cannot be handled by regular storage devices. Hadoop software framework, which is an open source framework by the Apache Software Foundation, can be used to overcome this problem. The key difference between Big Data and Hadoop is that Big Data is a large quantity of complex data whereas Hadoop is a mechanism to store Big data effectively and efficiently.
CONTENTS
1. Overview and Key Difference
2. What is Big Data
3. What is Hadoop
4. Similarities Between Big Data and Hadoop
5. Side by Side Comparison – Big Data vs Hadoop in Tabular Form
6. Summary
What is Big Data?
Data is produced daily and in large quantities. It is important to store the collected data accordingly and to analyze them to get better results. Google, Facebook collect a vast amount of data daily. Organizing the data and analyzing them can bring benefits to the organization. In a bank, it is essential to analyze data to understand customer information, transactions, customer issues. Analyzing these data and developing solutions will improve the profit. This shows that data is playing a vital role for an organization to work efficiently and effectively. As data is growing rapidly, the relational databases or regular storage devices are not sufficient enough. This kind of a large collection of data which is hard to store and process can be named as Big data or Big Data.
Big Data
Big data has three properties. They are volume, velocity, and variety. Firstly, Big data is a large volume of data. These data can take the volume of Giga Bytes, Tera Bytes or even higher than that. The second attribute is the velocity. It is the speed at which the data is generated. This is a major property in analyzing environmental changes and for detecting aircrafts. Data should be accurate and continuous in those situations. It is a considerable factor to make real-time decisions. Another main property is variety, which describes the type of data. Data can take text format, video, audio, image, XML format, sensor data, etc.
What is Hadoop?
It is an open source framework by the Apache Software Foundation to store Big data in a distributed environment to process parallel. It has an effective distribution storage with a data processing mechanism. Hadoop storage system is known as Hadoop Distributed File System (HDFS). It divides the data among some machines. Hadoop follows master-slave architecture. The master node is called Name-node and slaves are called Data-nodes. Data is distributed among all Data-nodes.
The main algorithm which is using to process data in Hadoop is called Map Reduce. Using map-reduce programs, jobs can be sent to slave nodes. Default language to write map-reduce programs is Java, but other languages can also be used. Data-Nodes or slave nodes will perform the analyzing task and sends the result back to the master-node/name-node. Master-node/name-node has a Job Tracker to run map reduce jobs on slave nodes. Slave-nodes/data-nodes have a Task Tracker to complete the data analyzing and to send the result back to the master node.
Hadoop Architecture
Hadoop has some advantages. It reduces cost, data complexity and increases the efficiency. It is easy to add another machine to the Hadoop cluster.
What is the Similarity Between Big data and Hadoop?
- Both Big Data and Hadoop are related to large sums of data.
What is the Difference Between Big Data and Hadoop?
Big Data vs Hadoop | |
| Big Data is a large collection of complex and variety of data which is hard to store and analyses using traditional storage methods. | Hadoop is a software framework to store and process big data effectively and efficiently. |
| Significance | |
| Big Data does not have much meaning. | Hadoop can make Big data more meaningful and is useful for machine learning and statistical analysis. |
| Storage | |
| Big Data is hard to store as it consists of a variety of data such as structured and unstructured data. | Hadoop uses Hadoop Distributed File System (HDFS) which allows storing a variety of data. |
| Accessibility | |
| Accessing Big Data is hard. | Hadoop allows to access and process Big Data faster. |
Summary – Big Data vs Hadoop
Data is growing rapidly. Government and Business organizations all are gathering data. Analyzing data is extremely valuable. A single computer is not enough to store a large amount of data. This large quantity of complex data is called Big data. Therefore, Big data can be distributed among some nodes using Hadoop. The difference between Big Data and Hadoop is that Big data is a large amount of complex data and Hadoop is a mechanism to store Big data effectively and efficiently.
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Reference:
1.“What is Big Data and why it matters.” What Is Big Data? | SAS US. Available here
2.The point, Tutorials. “Hadoop – Big Data Overview.” Tutorials Point, 15 Aug. 2017. Available here
3.The point, Tutorials. “Big Data Analytics Overview.” Tutorials Point, 15 Aug. 2017. Available here
4.“What is the difference between big data and Hadoop?” Techopedia.com. Available here
5.thippireddybharath. “Big Data and Hadoop Quick Introduction.” YouTube, YouTube, 12 Aug. 2014. Available here
Image Courtesy:
1.’BigData 2267×1146 trasparent’ By Camelia.boban – Own work, (CC BY-SA 3.0) via Commons Wikimedia
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