Which system to choose? A MongoDB vs. Couchbase comparison

The “MongoDB vs. Couchbase” comparison shows that both applications perform well in more than one area. While MongoDB scores above all with its flexibility, Couchbase proves particularly suitable for real-time applications.

MongoDB vs. Couchbase: United in the NoSQL approach

In this MongoDB vs. Couchbase comparison, we analyze two of the most popular NoSQL databases. In contrast to the traditional SQL, this approach uses fixed and rigid table constellations and instead relies on horizontal scaling. “NoSQL” usually always stands for “Not only SQL”, as there are considerable links to the long-prevailing approach. However, as data volumes continue to grow, many users need a database that is freely scalable, while remaining secure and easy to use.

What is MongoDB?

Since its initial release in 2009, MongoDB has become one of the most widely used database management systems for structured, semi-structured and unstructured data. The NoSQL database from MongoDB, Inc. (formerly 10gen) uses a non-relational and document-oriented data model and is therefore especially scalable. MongoDB was written in C++, is open source and is offered under the Server Side Public License in several free and proprietary versions. The system uses the BSON format, a binary form of JavaScript Object Notation (JSON), to save the stored data. Queries are made using the MQL language (MongoDB Query Language). The database is used by numerous large companies.

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What is Couchbase?

Couchbase was originally developed under the name Membase as a document-oriented open-source NoSQL database with a main focus on interactivity. The software is decentralized and can be scaled horizontally and vertically. Couchbase was released in 2010 and written in C++, Erlang, C, Go and Java. The database application’s query language is SQL++ and the data is stored in JSON documents.

Purpose and scalability

The comparison of MongoDB vs. Couchbase primarily analyzes two NoSQL databases. Both solutions are thus characterized by their high scalability. Due to the fact that MongoDB does not use tables and can also manage unstructured data, the solution is extremely flexible and manages too to scale large or increasing amounts of data. The system is therefore particularly suitable when the volume cannot be predicted in advance. However, users must first learn a new query method in order to use MongoDB.

Couchbase has become a popular solution for interactive applications in particular. The main reason for this is the extremely fast response times for read and write requests, which significantly reduce latency. Couchbase is cloud-native and therefore also very attractive for companies from other sectors. Our MongoDB vs. Couchbase comparison study revealed that the slightly younger option can also compete well in terms of flexibility.

Similar to MongoDB, Couchbase also relies on CRUD operations (Create, Read, Update, Delete), but has an integrated admin console which makes it much easier to use. Configuration in MongoDB, on the other hand, is manual.

Functionality

MongoDB stores and processes data in the BSON format. This data is stored in documents, which in turn can be bundled and retrieved in collections. Several collections can be stored in one database. The combination of database and collection is called a “namespace”. The documents differ from the approach of an SQL system, primarily, in that they can contain different data types. They are made up of key-value pairs, whereby the key is always a character string. Possible values include Boolean values, other documents, data or character strings. The collections can be searched using a text index.

Similar to its competition in the MongoDB vs. Couchbase comparison, the second solution also relies on the document as the basis. This is saved in JSON (JavaScript Object Notation) format without a predefined schema. Storage takes place on the hard disk or in the working memory, whereby the latter option extremely shortens response times. The documents are queried and manipulated using the proprietary SQL++ (formerly N1QL) language, which is very similar to the classic SQL. It uses simple commands such as delete, insert, merge, select or update. The query performance is comparatively high.

Query methods

The differences between MongoDB and Couchbase are particularly noticeable in the queries in the respective language. Here we illustrate this using an employee file. In our example, we add new employee, Maria Johnson, to the database.

In MongoDB this could look like this:

db.employee.insertOne (
{
first name: "Maria",
last name: "Johnson"
city: "Sacramento"
department: "IT"
}
)
mil

In Couchbase, the process looks like this:

INSERT INTO employee (KEY, VALUE)
	VALUES ( "1328",
		{	"firstname": "Maria"
			"surname": "Johnson"
			"city": "Sacramento"
			"department": "IT"
		} )
RETURNING *;
sql++

Architecture and availability

MongoDB and Couchbase also differ in terms of their architecture and availability. Both distribute the load across different server nodes and thus prevent possible failures. However, MongoDB relies on a model with primary and numerous subordinate nodes. Write operations are routed to this master node and then replicated. If the master node fails, another subordinate node takes its place. This can take up to 60 seconds. Couchbase uses various nodes, each consisting of an index service, a data service, a query service and a cluster manager component. Among other things, this manager regulates replication and switching to other nodes.

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Compatibility and programming languages

MongoDB and Couchbase are compatible with numerous server operating systems. Both databases support Linux, macOS and Windows. MongoDB also works with Solaris.

MongoDB stands out in the MongoDB vs. Couchbase comparison in terms of programming languages, as the list of supported languages shows:

Programming language Supported by Mongo DB Supported by Couchbase
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Kotlin
Lisp
Lua
MatLab
.net
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Swift

Security

With MongoDB and Couchbase, the security of the data depends on the edition the user has. The free options offer only rudimentary security features and require additional manual security measures to be taken. The standard version of MongoDB, for example, has no preconfigured access control. However, numerous security mechanisms are available in the proprietary versions. Among other things, MongoDB Atlas offers X.509, encryption on the client and server side, as well as Kerberos and LDAP integration.

Couchbase also encrypts, enables the authentication of users, allows roles to be assigned and monitors the databases. Additional security measures such as a firewall are nevertheless highly recommended.

Mobile use

Both options in the MongoDB vs. Couchbase duel offer additional possibilities for mobile use. MongoDB Realm is designed for mobile operating systems and MongoDB Atlas also has strategies for handling mobile systems. Couchbase Mobile allows the use of all conceivable devices and is designed for decentralized and secure edge-to-cloud use. The corresponding database is optimized for mobile software distribution and embedded systems.

Which companies use MongoDB and Couchbase databases?

MongoDB and Couchbase are used by large and well-known companies alike and for different purposes.

Among the companies that rely on MongoDB are the following:

  • Adobe
  • Amadeus
  • AppScale
  • Craftbase
  • Disney
  • Etsy
  • Foursquare
  • Lyft
  • MTV
  • The New York Times
  • Via Varejo

The following companies rely wholly or partly on Couchbase:

  • Amadeus
  • AT&T
  • Cisco
  • Disney
  • DreamWorks
  • eBay
  • LinkedIn
  • Marriott
  • Office Depot
  • Salesforce
  • Tommy Hilfiger
  • Verizon
Tip

Are you looking for more information about database management? We have explained numerous other topics for you in the Digital Guide. Alongside other comparison studies, you’ll find the MariaDB vs. MySQL comparison, an overview of the best open source databases and a detailed MongoDB tutorial.

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