What are the advantages of Hadoop?


Hadoop is designed to store and manage massive amounts of data. Hadoop is free, open-source, easy to use, and has amazing performance. There are many other advantages of Hadoop as well. So you are from business Intelligence (BI), SAP, Data Warehouse, ETL, Mainframe background, or any different technology domain. 

 

Let’s further delve into the Advantages of Hadoop.

Hadoop is easy to use, scalable and cost-effective. Along with this, Hadoop has many advantages. Here we are discussing the top benefits of Hadoop. So, the following are the pros of Hadoop that makes it so popular –

 

1. Varied Data Sources

Hadoop accepts a variety of data from multiple and diverse sources. Data can come from a range of sources like email conversation, social media, etc., and can be of the structured or unstructured form. 

 

2. Cost-effective

Hadoop is an economical solution as it uses a cluster of commodity hardware to store data. It requires fewer machines to store data as the redundant data decreased significantly.

 

3. Performance

Hadoop processes vast amounts of data with high speed with its distributed processing and distributed storage architecture. Hadoop divides the user task into various sub-tasks which are further assigned to worker nodes containing required data and these sub-task run in parallel thereby improving the performance.

4. Low Network Traffic

In Hadoop, there is always low network traffic. Each job submitted by the user is split into a number of independent sub-tasks which are further assigned to the data nodes. This allows the movement of a small amount of code to data rather than moving huge data to code, leading to low network traffic.

 

5. High Throughput

Throughput means job done per unit time. In Hadoop, a given job is divided into small jobs that work on chunks of data in parallel, thereby giving high throughput.

 

6. Open Source

Hadoop is an open-source technology i.e. its source code is freely available. The developers can modify the source code to suit a specific requirement. And moreover, if they face any problem, they can always rely on open-source code.

 

7. Scalable

Hadoop works on the principle of horizontal scalability. So nodes can be added to the Hadoop cluster on the fly, making it a scalable framework.

8. Ease of use

The Hadoop framework takes care of parallel processing through the backend automatically.

 

9. Compatibility

Hadoop is compatible with Spark, Flink, and similar emerging technology. They have got processing engines that work over Hadoop as a backend, i.e., We use Hadoop as a data storage platform for them.

 

So if you are looking ahead to using Hadoop technology for your projects, you must consult the best - GoodWorkLabs, a Hadoop solutions

 

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