MongoDB and CouchDB are both document-based NoSQL types of databases.

Relational databases store data in tables consisting of rows and columns, with rows representing individual records and columns capturing different attributes of the records stored. These tables usually have a key that allows the creation of relationships between the tables.

Examples of relational databases include MySQL, PostgreSQL, MariaDB, and Oracle Database, among others.

On the other hand, non-relational databases, also called NoSQL databases, are schemaless and do not have a rigid structure for storing data. Unlike relational databases, NoSQL databases do not store data in tables.

Instead, data is stored in formats such as key-value pairs, documents, or through graph structures. The way data is stored in NoSQL databases is very flexible, as they don’t have to stick to a predefined structure.

This makes NoSQL databases very useful in storing unstructured data formats such as text, video, and images.

NoSQL databases are also suitable for storing data generated by IoT devices or sensors and data generated in high volumes, such as social media posts and log data. Some of the most commonly used NoSQL databases include MongoDB and CouchDB.

This article will cover the main areas of comparison between CouchDB and MongoDB, which developers need to know before planning their next application stack.

MongoDB

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MongoDB is a structured NoSQL document database. By being structured, it means that MongoDB, like other databases, stores data in an organized manner. In MongoDB, data is stored in documents stored in a collection.

A document is a way to organize and store data in the form of key-value pairs. This format is known as JavaScript Object Notation(JSON).

A sample document is shown below:

{
    "name": {
          "first": “Oliver”,
          "last: "twist" },
    "home":  “London”,
    "age": 12,
    "isTall": false,
    "occupation": “apprentice”
}

In the sample document above, keys/fields are on the left of the colon, and values are on the right. Keys uniquely identify a data point.

Keys can be wrapped in quotation marks or written without them. The values are the data related to the identifiers used as the keys. If the value stored is a string, it has to be wrapped in quotation marks.

In NoSQL databases that use documents, the document key/field is the equivalent of columns in relational databases. In MongoDB, collections provide an organized way to store documents. A single collection can store many documents. The collections are, in turn, stored in a MongoDB Database.

MongoDB is often the preferred database in applications that require integrating large amounts of diverse data and applications that use complex data structures that evolve. This is made possible by MongoDB documents being schemaless.

MongoDB is also used in high-performance applications that have huge amounts of transactions and need fast access to data, such as in gaming, social media, e-commerce, and applications offering real-time analytics. MongoDB is the go-to database for agile development and multi-cloud and hybrid applications.

Some MongoDB companies include eBay, Adobe, Twitter, Google,  Forbes, Toyota, and EA Sports.

CouchDB

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CouchDB is an open-source NoSQL database developed by Apache Foundation and written in Erlang. CouchDB does not enforce any schema on the data it stores, unlike relational databases.

Data is stored in documents using JSON format, representing data using key-value pairs. CouchDB uses JavaScript as its query language and offers a RESTful HTTP API for users to create, read, edit, update and delete documents. 

CouchDB is both a single-node and clustered database. For less demanding projects, users often use a single-node CouchDB database instance.

However, for more demanding projects, clusters run a single logical database server on multiple servers or virtual machines. This allows for higher capacity and higher database availability without changing any APIs.

To query data stored in its database, CouchDB uses views as the main way of querying data and generating reports.

A great feature of CouchDB is that it allows building applications that can store data locally on devices and browsers when offline and then synchronize the data when the internet connectivity resumes. Therefore CouchDB is a great option when building applications that need to run both offline and online.

Some companies include Boieng, IBM, BBC, Credit Suisse, and npm, among many others.

MongoDB vs. CouchDB

Picking the right database to use involves a comparison between the available option to determine which database best meets a business’s needs. Here is how MongoDB goes head-to-head with CouchDB in terms of features.

Feature MongoDB CouchDB
Data Storage Data is stored internally in BSON format even though users represent it in JSON format Data is stored in JSON format
Speed MongoDB has much faster access to data, providing very fast read speeds Its read speed is slower than in MongoDB
Device Support It cannot be run on iOS or android. It only supports Windows, Linux, and macOS It can be run on android and iOS devices providing mobile support. This is in addition to running on windows, Linux, and macOS
Replication Supports master-Slave replication Supports master-master replication and master-slave replication
Preference Favours consistency which ensures data is accurate and consistent across all transactions Favours availability where authorized users can access the database at all times
Query Language Has its own MongoDB Query Language(MQL) to query the database. Uses an HTTP Rest API to query its database
Security Offers enterprise-grade security, which makes it more secure than CouchDB It is not as secure as MongoDB
Scalability Suitable for a rapidly growing database where its structure is not clearly defined from the start Not ideal for a rapidly growing database

Whereas MongoDB and CouchDB are both NoSQL databases, each is suitable for different use cases.

Benefits of using MongoDB

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Some of the benefits of using MongoDB include the following:

High Performance

A key factor driving the adoption of MongoDB is its speed. Since it uses a document model where all information about a data point can be stored in a single document, it makes querying the data faster as there is no need for join operations. This, in turn, allows for high-speed read and write operations.

Flexible Schema

MongoDB does not enforce any schemas on the data stored. This allows it to be a flexible database that matches and supports the changing nature of data stored as applications evolve and grow. MongoDB also supports the fast scaling of applications.

Sharding

sharding allows for large datasets to be distributed among multiple servers for processing without compromising performance. MongoDB supports sharding as it is designed as a distributed database allowing users to create clusters to enable sharding.

Language Support

MongoDB has drivers that support almost all popular programming languages allowing users to use it with their programming language of choice easily. By storing data in documents, MongoDB allows users to use the data in data structures native to the programming language they are using.

Cloud-Based Platform

MongoDB offers its users a cloud storage option through MongoDB Atlas, which allows users to integrate their database with the cloud easily. MongoDB also allows users to multi-cloud deployment to major cloud providers.

User Support

MongoDB has excellent support for users, from developers learning how to use it in development to users using it for storage. It has excellent documentation, an active community, and MongoDB University, which offers free courses on how to use MongoDB.

The above features make MongoDB an excellent choice when considering a NoSQL database solution.

Benefits of using CouchDB

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Some of the benefits of using CouchDB include the following:

Mobile Support

Unlike other databases, CouchDB can run on Android and iOS operating systems in addition to Windows, Linux, and macOS. In addition to running on mobile devices, it allows syncing data between the local storage on the mobile devices to a remote database.

Open Source

CouchDB is open-source in nature and free to use. This can be advantageous to users as it allows them to avoid vendor lock, which can happen with proprietary databases. Being open source also allows CouchDB to be easily integrated with existing infrastructure.

Bidirectional Replication

This makes synchronizing data across multiple servers fast and easy. This makes retrieving and backing up data fast and easy as all servers are synced to reflect the most recent changes in data without any conflicts arising.

Fault tolerance

CouchDB’s internal architecture is fault-tolerant, which is useful in running applications as it contains and deals with failures in a controlled environment. This prevents failures in running applications from propagating and escalating through a server

High scalability

CouchDB is designed to handle large amounts of data and high traffic. It allows for horizontal scaling by adding more servers to the cluster; this way, it can handle the increased load.

ACID compliance

CouchDB is fully ACID compliant, guaranteeing Atomicity, Consistency, Isolation, and Durability. This makes it a good choice for applications that require a high level of consistency and data integrity, such as financial systems or healthcare applications.

CouchDB has standout features such as mobile device support, and its open-source nature offers it a uniqueness compared to proprietary databases.

Final Words

MongoDB and CouchDB are both excellent choices for NoSQL databases and have lots of benefits compared to traditional relational databases. However, even though they are both NoSQL databases, they have different capabilities and are suited for different applications and uses.

If you’re looking for a powerful, feature-rich database that can comfortably handle large amounts of data and offer high performance and efficiency, MongoDB is an obvious choice. MongoDB is also the go-to database if your application will need to scale very fast and utilize advanced indexing options.

If you’re, however, looking for a lightweight no, resource-intensive database that can be run on mobile devices and offer offline support, then CouchDB is the right choice. Additionally, if you’re looking for a database that can support master-master replication with data duplication to ensure the constant availability of data, CouchDB should be your go-to database.

You may also explore some top open source database software for your next project.

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