Hadoop Framework has a bunch of advantages over other big data tools. Its core components like HDFS(Hadoop Distributed File System), MapReduce and YARN add extraordinary features to its functionality.
In fact, it has been serving as one the best big data tools for distributed processing and storage of large data sets across computer clusters.
Hadoop is designed in such a way that it can handle large volumes of data efficiently and in a very cost effective manner. This is also one of the reasons behind its popularity in the big data market.
Hadoop Framework Advantages
We have described below some of the advantages of Apache Hadoop technology as compared to traditional data processing techniques(like RDBMS) and other modern big data tools.
Open Source
Apache Hadoop is an open source software. If there comes need to modify or manipulate the code, it can be easily done to meet the business requirements.
Easy to use
Working on Hadoop is very easy as it doesn’t involves client interaction while dealing with distributed computing. The Hadoop framework is smart enough to manage all such tasks.
Reliable
The data is automatically replicated in the computer clusters which reduces the risk of losing the data thus making Hadoop a reliable software framework to work on.
Flexible
Using hadoop, the unstructured data can also be easily handled which cannot be performed by the traditional data processing techniques. It makes the unstructured data useful for making important decisions for business growth. Therefore Hadoop proves to be very flexible.
Distributed Processing
HDFS, one of the core component of Hadoop allows the large data to be stored in a distributed manner. Thus the data processing goes parallel across the nodes in a cluster.
Fault Tolerance
Hadoop is fault tolerant or you can say failure resilient. It means if the data is lost, it can be easily recovered from the replicated blocks of data across the nodes in the cluster. The framework performs this task automatically.
Robust Ecosystem
Hadoop ecosystem is very robust. It comes with several other projects such as Hive, HBase, Spark, Mahout, Pig, Cassandra, Zookeeper etc.
These hadoop-related projects are highly aimed to deliver all the big data solutions to meet the needs of small and large organizations regarding storage and processing of large data sets.
Fast Data Processing
Since Hadoop has the ability to perform parallel data processing in the clusters, it has now become easy to process large amount of data at a very faster rate as compared to traditional data processing technologies.
High Availability of Data
There is the high availability of data in Hadoop Framework. The data is replicated in other systems can be used in situations when it has been lost from one of the systems. The system continues processing automatically without any machine or hardware failure.
Inexpensive
Since Apache Hadoop runs on computer clusters built from commodity hardware and does not require any specialized machine, it is comparatively cheaper than other big data technologies.
Data Locality
Data Locality in Hadoop means moving the computation(MapReduce algorithm) to the data across the nodes in the cluster rather than moving data to the computation location where the MapReduce algorithm is submitted by the client. This makes the execution faster as it is better to move an algorithm instead of large data.
Scalable
Apache Hadoop is scalable. It means you can easily scale the cluster as a result of increased requirements. This scaling of a cluster can be done by applying one of following two mechanisms.
- Vertical Scalability- It involves adding resources or hardwares like Memory, Disk, CPU etc. to the nodes in the cluster to meet certain requirements.
- Horizontal Scalability- It involves adding more machines to the existing computer clusters.
Cost Effective
It takes a very little cost per terabyte of storage to manage all the big data using Hadoop framework as compared to other big data technologies. This feature makes hadoop a cost effective software framework for storing and processing big data.
Looking at the above advantages, we can definitely assure a promising scope of hadoop in the future. So the IT professionals who are looking forward to learn Hadoop should not waste their time and quickly join the best hadoop training institute to leverage their skills in big data technology.