Today, data rules the tech world and there are certain tools that are essential for the management of this data. When choosing a NoSQL database, we need to take care of the flexibility, expandability, presentation, and
its accessibility. Following are the topics that we will explore today to gain a complete understanding of the distinctions between Couchbase and MongoDB. This will allow one to make sound decisions when it comes to choosing between these two NoSQL databases.
In this high-tech world, the demand of the people is increasing more and more and to satisfy the demand of the customers has become the borderline that determines the success of any database.
Let’s first take a look at what MongoDB and Couchbase is. Then we will draw up a comparison between the two.
What is MongoDB?
MongoDB is a NoSQL document database. It is used for high-volume data storage. This database came into light around the mid-2000s.
MongoDB uses collections (sets of documents and functions) and documents (consists of key-value pairs) instead of tables and rows. Key-value pairs are the basic unit of data in MongoDB while the set of documents and functions is the equivalent of relational database tables.
MongoDB is an important database server with the great specification that is, the elective storage engine named the WiredTiger. This engine improves the writing capability of the MongoDB server by about ten times more than the normal one.
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What is Couchbase?
Couchbase Server is a NoSQL document-oriented database used for interactive web applications. It is the merge of two popular NoSQL technologies:
- Membase – It provides replication, persistence, and sharding to the high-performance Memcached technology
- CouchDB – It pioneers the document-oriented model based on JSON. Following are some of the features of Couchbase:
- It is easily scalable
- It provides a consistently high performance
- Its data mode is flexible
- It is able to serve application data with 100% uptime
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Key Differences: Couchbase vs MongoDB
Let’s take a look at the key differences between MongoDB and Couchbase in the following table.
|Distribution||It is uniformly distributed.||It is multo-dimensionally distributed.|
|Function||It performs distributed query processing and merging from intermediate results.||It manages data, query, and index on every shard or node.|
|Role||It acts as the coordinator.||It acts like the worker bee.|
|Data Model||It is both document as well as key-valued.||The data model is only document type.|
|Query||The query is of N1QL, key-values, and Ad-hoc views.||The query is of Ad-hoc and MapReduce aggregation|
|Concurrency||It is both optimistic and pessimistic locking.||It is both optimistic and pessimistic locking but with WiredTiger, an optional store machine.|
|Storage||It can store binary values up to about 20 MB.||It can store huge files into a huge number of documents.|
|Scaling||It is easy because of its master-master scaling model.||It is complicated due to its master-slave structure.|
|Fragmentation||It does all the fragmenting by itself.||It relies on us for choosing the fragment key and the fragmenting method.|
|Mobile Resolution||It supports mobile application.||It does not support mobile applications|
|Performance across large number of datacenters||Due to its simple architecture and duplication facility, it performs all the write operations locally.||It fails to do all the write operations due to its architecture.|
|External Cache||It does not need external cache.||It requires external cache.|
|Time Consumption and Management||It is easy to deploy and does not consume time.||It consumes time and management.|
In Detail Comparison of Couchbase and MongoDB
The data which need not be kept in the memory is used for data standardization. For that, the number of read and write operations performed by both 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 inactive mode is a maximum of 5 milliseconds. The performance of the Couchbase and the MongoDB server will be determined at what level they both perform as the number of customers keeps on increasing continuously until and unless the read and write inactivity overcomes the standard time of 5 milliseconds.
Find out all about Couchbase in this insightful Couchbase Tutorial.
The 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.
Here is a detailed comparison of Couchbase and MongoDB:
In terms of data models, Couchbase is both document as well as key-valued. 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 query as well as index services also.
On the other hand, MongoDB has a data model that is only document-type. The key decision when designing these revolves around the structure of documents as well as the representation of the relationships between data by the MongoDB application. All related data can be embedded within a single document when using MongoDB.
The Couchbase server query is of N1QL, key-values as well as Ad-hoc views. In Couchbase Server 7.0 and later, the documents are stored in collections that are in scopes. Scopes are stored in buckets within a namespace. The full path of the collection should be known by the query engine.
The MongoDB query is of Ad-hoc and MapReduce aggregation. It helps retrieve the data from the MongoDB database and works similarly to SQL queries. When performing a query operation, criteria or conditions can also be used to retrieve specific data from the database.
Go through these Couchbase interview questions to crack your job interview.
In terms of concurrency, the Couch base server is both optimistic as well as pessimistic locking. Couchbase can support a huge number of customers with a single node without affecting its performance at all.
The MongoDB server is also
of both optimistic as well as pessimistic locking but with an optional store machine called the WiredTiger. Its work quality rapidly degrades with a growing number of customers. MongoDB cannot entertain a lot of customers, the instance the number of customers increases, it starts performing reversely.
We need to add more tools for serving a lot of customers through MongoDB which is really costly.
The Couchbase server has the capacity of storing binary values up to about 20 MB. It stores certain items in compressed form on the disk. When the need arises, it removes them. Data sets can, therefore, exceed the size permitted by existing memory resources. This is because the undeleted items can be restored to memory from disk when they are not currently in memory. It also enables backup-and-restore procedures.
The MongoDB server has got the ultimate capacity of storing huge files in a huge number of documents. Although the MongoDB server can store larger binaries, still one can continue to use the 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. 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.
MongoDB is tough to scale from a particular duplicate set to an entirely fragmented frame. Since MongoDB has a master and a slave structure, 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.
Check this MongoDB Aggregation tutorial to understand recording data and providing computation outcomes, operations, and pipeline concepts in MongoDB.
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 MongoDB, a fragmenting method, and a key has to be selected since its data model is entirely document-based. This fragment key will tell you the exact location of the document in the cluster.
The difference between the two is that 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.
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Facility Of a Mobile Resolution
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 develop apps that you can use with or even without the internet.
Go through this tutorial on MongoDB Replication to learn how to make replicas in MongoDB.
Management And Consuming Of Time
Couchbase with its simple structure is very easy to deploy since its installation, set up, and adding and erasing nodes is too simple.
MongoDB asks for a lot of physical and added arrangements and its application is really hard and full of complexities and multi-parts.
Capacity To Perform In a Large Number Of Data Centers
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.
When applied to a large number of data centers, MongoDB fails to do all the write operations due to its architecture.
Need Of An External Cache To Assist It In Accomplishing
Since the MongoDB server cannot serve concurrent customers so, we need to add another cache to assist in serving the customers which really costs more money and complications.
Couchbase with its completely incorporated and organized entity cache asks for no external costs at all. It is a better and less expensive caching solution.
We hope this article was able to give you a good comparison between Couchbase and MongoDB. While MongoDB and Couchbase have many things in common, knowing the distinction can really help both developers and experts alike.
Check out the MongoDB Tutorial to learn more about MongoDB Data Modelling.