Advantages & Disadvantages of Hadoop Framework

Hadoop is a collection of open-source software utilities for performing calculations on massive amounts of data. Hadoop offers a software framework for different storages in various locations and processes them. Hadoop processes various structures and non-structures to collect, process, and analyze big data. There are many pros and cons to using Hadoop; understanding them will help you for making a decision. 

Advantages And Disadvantages of Hadoop Framework

Here, we will disclose the benefits and drawbacks of the Hadoop framework. Read and understand before hiring Hadoop developers for your project.

Pros of Hadoop

1. Range of Data Sources

Data collected from various sources will be structured or unstructured. Sources can be social media, email conversations or even clickstream data. It would take a lot of time to convert all the collected data into a single format. Hadoop saves this time by deriving valuable data from any form of data. It also has various functions like data storage, fraud detection, market campaign analysis, etc.

2. Speed

Every organization uses a platform to get work done at a faster pace. Hadoop enables the business to do just that with its data storage needs. It uses a storage system in which the data is stored in a distributed file system. Since the tools used for data processing are located on the same servers as the data, the processing operation also takes place faster. So you can process terabytes of data in minutes using Hadoop.

3. Multiple Copies

Hadoop automatically duplicates the data stored on it and creates multiple copies. This is done to ensure that, in the event of a failure, data is not lost. Hadoop understands that the company's information is essential and should not be lost unless it discards it.

4. Profitable

In conventional methods, companies had to spend a considerable amount of their profits on storing large amounts of data. In some instances, they even had to delete large raw data sets to make room for new data. As per a leading mobile app development company, there was the possibility of losing valuable information in such cases. Using Hadoop, this problem was entirely resolved. This helps in the long run because it stores all the raw data generated by a business. If the company changes the direction of its processes in the future, you can easily query the raw data and take the necessary action. This would not have been possible with the traditional approach because the raw data would have been removed due to increased expenses.

Cons of Using Hadoop Framework

1. Not suitable for small data

While big data is not designed exclusively for large companies, not all big data platforms are suitable for small data needs. Unfortunately, Hadoop is one of them. Due to its high-capacity design, Hadoop's distributed file system. As a result, it is not recommended for organizations with small amounts of data.

2. Security concerns

Simply managing complex applications like Hadoop can be challenging. An instance can be seen in the Hadoop security model, which is deformed by default due to its complexity. If the platform administrator does not know how to enable it, their data could be at significant risk. Hadoop also lacks encryption at the storage and network tiers, a significant selling point for government agencies and others who prefer to keep their data secret.

3. Vulnerable by nature

Speaking of security, Hadoop's very structure makes running it a risky proposition. The framework is written almost entirely in Java, one of the most widely used programming languages​​. Java has been implicated in numerous security breaches as a result.

Concluding Thoughts

The blog explains that companies could miss out on huge benefits and drawbacks by using only Hadoop. If you dream of developing Hadoop applications, Contact the Hadoop team. So thanks for reading the blog.