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 analyse 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.

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 de­cent­ral­ised 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 analyses two NoSQL databases. Both solutions are thus char­ac­ter­ised 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: "Wolverhampton"
department: "IT"
}
)

In Couchbase, the process looks like this:

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

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.

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:

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 de­cent­ral­ised and secure edge-to-cloud use. The cor­res­pond­ing database is optimised 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