Today in this world where your existence is judged by your online presence, the amount of data is increasing more and more every day and its storage and management have become one of the very big issues. Working with Data scientists is hard and are inventing newer techniques for handling such big data every single day. Social media, IT industries, and every way of using the internet have been collectively taking part in enhancing the dimension of data. The existing ways of storing data are lesser in number compared to the total amount of data. The available rows and columns are not enough to take care of the continuously enlarging data because most of the data generated are unstructured.
As the size of data keeps on changing, scientists have discovered that conventional databases have to be replaced with newer and advanced ways of storing tools. NoSQL and Hadoop are faster-growing technologies that companies use for the storage and management of their data. Although Hadoop gets more recognition for data storage, observing various surveys it is found that practically NoSQL is better and more advanced. NoSQL assembles effective relevance that constrains the production all the way through the whereabouts of commitments. In this article of mine, I will be discussing two NoSQL databases named MongoDB and Cassandra.
MongoDB
MongoDB is a reasonable move, towards a large number of applications. Its activities and performance are similar to the conventional and old style of storage systems. So it is quite easy and comfortable to use. This database is quite elastic and expandable as a result of which it has become user-friendly and also helps users in the network. Only because of its ease of use, MongoDB is popular among engineers who take no time in working with this database. It has got master and slave architecture.
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When we use MongoDB, we use the same data model in both the database as well as in the code, hence it requires no layering of complicated mapping. As a result, it becomes very simple to use which makes it immensely popular among users.
It is never tough in going with MongoDB because companies that know this tool can take their investments in return making it tension free to stay reliable only on a few databases. It is prepared for use in online transaction processes. It performs and solves complicated situations but still, it cannot be regarded as the perfect one. It does not help in complicated transactions.
Advantages of MongoDB
- Scalability
- Flexibility
- User-friendly
- No concept of rows and columns
- No re-establishment of indexing
Disadvantages of MongoDB
- Memory is not expandable
- Joins can be done only through multiple queries
- No transactions can be done
Cassandra
MongoDB is popular due to its ease of use but Cassandra is popular for its ease of management facility that too in expanded form. When users tend to construct conventional data more dependably with more speed, they will come closer to Cassandra. Cassandra has a structural design where the whole sum of space is stretchable by the accumulation of external devices allied on rows and columns by means of their own assets. It supports multiple numbers of data centers working together. With a masterless architecture, Cassandra offers a great performance through its quality of great scalability, awesome writing, and also great solving of queries.
Deploying newer technologies for you becomes very simple and comfortable once you know the interiors of Cassandra technology. Training Cassandra is just a question of only some hours. Proper training and certification of Cassandra lead you to immense understanding and an ocean of opportunities. Once you become completely aware of the Cassandra data model and its functioning processes, you can successfully develop Cassandra’s applications.
Advantages of Cassandra
- Free of cost
- Peer-to-peer structural design
- Elasticity
- Fault tolerance
- Great Performer
- Column based
- Adjustable steadiness
Disadvantages of Cassandra
- No support for Data Integration
- No streaming of globule values
- No cursor support
- Large outputs must be physically paged
This was about a few of the differences between the two databases – Cassandra and MongoDB. If you guys have any other points that I may have left, please do share them by writing them down in the comment box.