Small as well as large companies alike need a proper database management system to ensure that they are able to manage all the information associated with their business. There are different types of interfaces for this purpose and a number of people who are seasoned businessmen, hire professionals or learn it themselves so that the database of the company is well maintained. Earlier before the advancements in technology, database management was an elaborate, time-consuming manual task which has to be done with files and folders and was difficult to store. Technology, as well as digital media, have made the same process concise that can be controlled in a clean manner and does not need an entire room to be stored. At the basic level, Microsoft Access is a simple database management choice that you have, and you can always use it for companies. But there is another specialized database software that is developed today, and you can also opt for them as well and will discuss that how Hadoop is different from the traditional database?
What is Hadoop?
Many people mistake Hadoop as a database system because of how it works. However, it is not a database system in a conventional way but is a distributed file system that is used for storing large sets of data in the various computer clusters within the office. One has to be trained in how to use this software to make the most of its features. There are various crash courses for training the users on how to use the software. It comprises two core components- namely, the Hadoop distributed file system as well as map-reduce. The distributed file system works as the storage layer of the system for all the data that is available within the computer clusters of the company. The map-reduce is the programming solution that is used for processing the large data sets which are available. They are split into blocks, and then these locks are distributed across the computers.
What is a traditional database?
The traditional database is solely used for storing data in the form of tables and comprises several rows as well as columns. They operate based on the SQL or the structured query language which helps to update and access the data that is available on the database. The basic difference between the two options lies in the programming software and the method of operation. Here we are going to discuss the major differences between the two choices and which is suitable for your company. It is important to know which software will work best so that the database of the company is well maintained and you can earn profits consistently from your company.
Data volume and architecture
The data volume refers to the amount of data that can be and is being stored in the system and then processes. The amount of data that it can hold defines its capacity. Traditional database system functions better when the volume of the data is low that is, in gigabytes at most. The database system may fail to give smooth results if the data size is in terabytes or petabytes. On the other hand, the Hadoop system works better even if the data size is huge. It can smoothly process even petabytes of data effectively and then store them well. This is a major reason behind its growing popularity particularly among the larger companies which have a huge database that has to be smoothly run.
The architecture is varied as well for both the system. Hadoop is composed of several core components like the Hadoop distributed file system and may reduce to process large data. It also has Hadoop yarn that is used for managing and computing the various computer clusters. The traditional database possesses ACID which stands for Atomicity, Consistency, Isolation, and Durability. All these properties are responsible for maintaining and ensuring data integrity and ensure that they are accurately maintained when a transaction takes place within the database system. The database system is often related to the banking system, the manufacturing industry. Telecommunication and the education sector. All these sectors need the database system majorly, and they look for professional help regarding the same. You can easily opt for remoteDBA.com which has a smooth database management service for all the users.
Throughput and data variety
The total volume of the data that is being processed within a particular span of time to make sure the output is maximum is called throughput. The traditional database system is not able to achieve a high rate and often fails when compared to the Apache Hadoop framework. This is another reason that fuels the heavy use of the Hadoop system over the traditional database management options that are available today.
The data variety, in general, refers to the process and means through which the data is going to be processed within the system. It can be structured, or semi-structured, and even unstructured. The Hadoop system can process and store all the variety of data irrespective of the processing method it has undergone. The traditional database, on the other hand, can be used only to manage unstructured data. This is again clearly a characteristic where Hadoop is way ahead of the traditional management system for any kind of data.
The use of the MongoDB database.
Wrapping things up
Data management is an important aspect of the business, and almost every core company and industries require a proper data management system to function smoothly. If you are new to the world of data management, you will find it difficult to tell apart the various systems that exist. One such option is Hadoop. When you understand the differences between Hadoop and the traditional database system, it is clear that Hadoop is a winner and a smoother option in contemporary times.
Data management is a massive field. There are various resources available on the web for you to know more on this topic.
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4 Replies to “How Hadoop is different from the traditional database? How can a Remote DBA expert help you with Hadoop?”
This was a great help. I take freelance hadoop projects. now I can partner with traditional DBAs as well to expand my business. Never though that way.
Great post, thank you.
Thank you for this great piece of information. Much appreciated.
nice blog! it’s interesting. thank you for sharing.