Today data rules the tech world and there are certain tools that are essential for the management of these data. A NoSQL database plays an important role in handling, managing and working with the data. While choosing a NoSQL database we need to take care of the flexibility, expandability, presentation and its accessibility. In this high tech world, the demand of the people are increasing more and more and to satisfy the demand of the customers has become the border line that determines the success of any database. In this article, I will be describing two such great NoSQL databases and they are CouchBase Training Server and MongoDB. The comparison between the two NoSQL server databases tells us which database we should go for meeting the demands of the customers in this IT world.
The MongoDB is an important database server with its great specification that is, the elective storage engine named as the WiredTiger. This engine improves the writing capability of the MongoDB server about ten times more than the normal one.
The data which need not be kept in the memory is used for data standardization. For that the number of the read and write operations performed by both the servers is almost identical. When the data is used somewhere outside the memory, it will tell us how and in what ways the two servers perform outside the memory.
The time till when the read and write activity can stay in the inactive mode is a maximum of 5 milliseconds. The performance of the Couchbase and the MongoDB server will be determined in what level they both perform as the number of the customers keep on increasing continuously until and unless the read and write inactivity overcomes the standard time of 5milli seconds. These two servers are both stores for documents and they can be used on single as well as multiple servers. And although they are both NoSQL servers, they operate differently from each other.
In terms of data models, the Couchbase is of both document as well as key-valued, while the MongoDB’s data model is only document type. Since the data model of the Couchbase server is both a document and key-valued hence every document will start with a key value since all documents have got keys. It can also be used for the query as well as index services also.
The Couch base server query is of N1QL , key-values as well as Ad-hoc views. While the MongoDB query is of Ad-hoc, and MapReduce aggregation.
In terms of concurrency, the Couch base server is both optimistic as well as pessimistic locking while the MongoDB server is also of both optimistic as well as pessimistic locking but with an optional store machine called as the WiredTiger.
MongoDB’s work quality rapidly humiliates with growing number of customers. MongoDB cannot entertain a lot of customers, the instance the number of customer increases, MongoDB starts performing reversely. We need to add more tools for serving a lot of customers through MongoDB which is really costly.Couchbase can support a huge number of customers with the single node without affecting its performance at all.
The Couchbase server has the capacity of storing binary values till about 20 MB, but the MongoDB server has got the ultimate capacity of storing huge files into a huge number of documents. Although the MongoDB server can store larger binaries, still one can continue to use Couchbase server with a separate storage service for holding metadata on the binaries.
The Couchbase has a distributed master-master scaling model, while the Mongo DB has got both master and slave duplicate sets as its scaling model. MongoDB is tough to scale from a particular duplicate set to an entirely fragmented frame.
Since the MongoDB has a master and a slave structure, so it is a big complicated process with a large number of movable parts and also physical structure, hence it is hard to scale from one duplicate copy for obtaining a fully fragmented frame. But Couchbase is masterless and it always keeps a duplicate of its original document so that whenever data fails, the duplicate file can be used as a substitute.
The Couchbase fragments the data and then counts horizontally by spreading hash space to all the nodes in the cluster of the data. The placing of the hash space to a particular node is decided by the key present in each document.
For fragmentation of the data using the MongoDB, a fragmenting method, and a key has to be selected since its data model is entirely document base. This fragment key will tell you the exact location of the document in the cluster.
The difference between the two is that the MongoDB relies on us for choosing the fragment key and the fragmenting method, while the couchbase server does all the fragmenting by itself without human intervention.
Facility Of A Mobile Resolution
The MongoDB does not support mobile applications and hence you have to write your own code for the apps hence, you have to make sure that you always have an internet connection to use your apps. Couchbase entirely supports mobile and it helps developing apps that you can use with or even without the internet.
Management And Consuming Of Time
The MongoDB asks for a lot of physical and added arrangements and its application is really hard and full of complexities and multi-parts. While the Couchbase with its simple structure is very easy to deploy since its installation, set up and adding and erasing nodes is too simple.
Capacity To Perform In a Large Number Of Data Centers
When applied to a large number of data centers, the MongoDB fails to do all the write operations due to its architecture. Couchbase due to its simple architecture and duplication facility performs all the write operations locally when applied to a large number of data centers. Hence, the inactivity is minimized and performance is increased.
Need Of An External Cache To Assist It In Accomplishing
Since MongoDB server cannot serve concurrent customers so, we need to add another cache to assist serving the customers which really costs more money and complications. But Couchbase with its completely incorporated and organized entity cache asks for no external costs at all.