CouchDB vs. MongoDB: 10 things you should know

CouchDB is an Apache Software Foundation Product inspired by Lotus Notes. It is one of the NoSQL DB providers. It is a non-relational database meaning it does not use rows and columns to store data, as is the case with relational databases. Erlang is the most widely-used programming language by CouchDB.

It is also an open-source document-oriented database, and in the document field, it is stored as key-value maps. The fields can be a simple key, value pair, list, or map. Documents stored in the database are given document-level unique identifiers (_id) and revision (_rev).

Features of CouchDB

1. It facilitates authentication and session support to keep the authentication open through a session cookie.
2. It provides a more straightforward form of replication.
3. It provides a browser known as GUI, which handles data, permission, and configuration.
4. It provides database-level security such that permissions per database are separated into administrators and readers, which are allowed to read and write data to the CouchDB.
5. It validates the data that has been inserted into the database without using authentication to verify the creator and login session.

What is MongoDB?

MongoDB is a document-oriented, NoSQL DB with the scalability and flexibility needed to query and index data.

Features of MongoDB

1. Provides users with high-performance since it does not contain both join or transactions, thereby providing fast data access which in the long run improves performance.

2. There is high availability because of the incorporation of replica sets which can provide backup during failures.

3. There is an ease in scalability.

4. Data model design aids in reducing the need for joins, thus easing the evolution of schema.

5. The language is highly rich in queries, and it has its query language, which is known as Mongo query language that can replace the SQL language.

CouchDB vs. MongoDB

1. Technical details

Both CouchDB and MongoDB are documented-oriented, NoSQL databases that contain significant differences in their implementations. For instance, when CouchDB uses the semi-structured JSON format to store data, MongoDB uses the Mongo query language. The query language is distinct from SQL; however, they are similar. The queries to a CouchDB database are made through RESTful HTTP API using either JavaScript or HTTP.

The RESTful APIs are responsible for inserting data, editing the data, reading the data, and deleting the data. In MongoDB, the data is freely stored in BSON format. However, this structure is not defined in the MongoDB database. Hence, its size can vary as per the size of the document.

The CouchDB uses indexes that are similar to the SQL indexes. These indexes are used to retrieve documents and filter the documents in a specific order. MongoDB uses the indexes to read data because the read time of the database performance will be affected without the use of indexes since the reading time will have increased.

There are areas where CouchDB and MongoDB have a variety of similar features. The primary unit of data in both databases is the document. There are fields such as Booleans, numbers, lists, and many others in the document. One can store documents in either of the databases without first defining a schema or structure for that document like it is with relational databases. This feature gives greater flexibility over the data stored in both databases. It is the reason why they are referred to as schemaless databases.

2. The CAP Theorem

The CAP theorem is the main difference between CouchDB and MongoDB. This theorem states that any distributed database can only have a maximum of either two or three desirable qualities. The desirable qualities are; consistency, availability, and partition tolerance. Consistency refers to all clients having the same view of the data, whereas availability refers to all clients being able to read from and write to the database at all times.

The approach of the two document-oriented databases differs in their approach to the CAP Theorem. Whereas CouchDB favors availability and partition tolerance, MongoDB favors consistency as well as partition tolerance. Subsequently, partition tolerance refers to the database cluster being able to keep working despite breakdowns between the communication nodes. MongoDB also uses the replication model. This means that there are multiple nodes, and data is stored in the replicated nodes. One node usually acts as a primary node, while the other nodes act as secondary nodes.

Through this model, the consistency in MongoDB is always maintained. In addition, CouchDB uses eventual consistency, which means that clients can write a single database node, and the information is guaranteed to propagate to the rest of the database eventually. In CouchDB, data is stored in one of the nodes, and all the nodes sync with each other to make sure that data is also available in the database. MongoDB uses consistency, and the database uses a replica set to provide redundancy but at the cost of availability.

3. Scalability and performance

According to scalability and performance, MongoDB is generally much better than CouchDB, especially when working with big datasets and high-performance requirements, including reading faster and with high speeds. MongoDB is also better when compared to CouchDB when it comes to deployments, especially when you are either not sure of your resource consumption or anticipating a faster growth in the coming years.

CouchDB offers a master to master and master to slave replication, whereas MongoDB covers multi-slave configurations only. Master to master is also known as multi-master replication, and any node in the cluster can act as the master; therefore, it accepts the read and writes requests. Due to this functionality, an automatic failover is always enabled.

4. Popularity

Even though evaluation of the databases should not come to a contest of popularity, selecting the most popular database will provide a significant secondary benefit. In cases where one uses technologies with larger communities, one will find support and hire experienced people with such solutions.

A popular resource that tracks the popularity of database technology is MongoDB which is the fifth most popular database in the rankings. In the ranking, CouchDB is the fourth most popular database.

5. Pricing

The two databases are open-source projects that are free of charge to be used. However, the total cost of deployment should be considered when using the databases for production in business workloads. Paying for a managed database service and technology of your own choice is common because you will be able to access cloud-based infrastructure, high-quality support, streamlined maintenance, and other valuable features.

The CouchDB is available on both Amazon Web services and Google Cloud Platform. Google has projected the cost of deploying CouchDB on Google Cloud Platform to 34.72 dollars per month for 24 hours a day. The CouchDB managed services available on Amazon Web Services start from 0.019 dollars per hour. The managed cloud database service for MongoDB is the MongoDB atlas. It is accessible at a low capacity starting from 512 MB to 5GB of storage. It has a shared ram, and the dedicated tier starts from 57 dollars per month. It also offers 10 GB to 4 TB of storage, 2GB to 768GB of RAM.

6. Failover mechanism

The failover procedure is prolonged in the CouchDB since when one master fails or goes down, it takes time to switch over to the next for data storage operations. On the other hand, the failover mechanism is fast in the MongoDB database.

7. Programming languages

The two document-oriented databases use different programming languages for development. MongoDB uses the C++ programming language to develop the database, and various operating systems such as Windows, Linux, Solaris, and OS are supported. CouchDB uses the Erlang programming language for development, and operating systems such as Linux, OS, Windows, Android, iOS, Solaris, and BSD are supported too.

8. Errors and bugs

Errors and bugs are also another significant difference between the two document-oriented databases. Bugs and error support are essential for the database schema because the data operations are carried out nonstop hence the need for help to handle the errors. MongoDB is relatively better at supporting errors and bugs when a comparison is made. The developers, as well as programmers, prefer MongoDB to CouchDB for operations of data storage.

9. Security standards

The two databases have high-security standards though the CouchDB has additional security features that make it more secure than the MongoDB database. However, with both databases, you are assured of high-security standards. Therefore when it comes to security-related issues, you don’t need to worry. Choose any database of your liking, and you are all set to go.

10. Containers

Containers are present in MongoDB, and they act as additional layers, whereas in CouchDB, there is no such functionality. The extra layers aid in managing tasks properly and executing the operations properly in the MongoDB document-oriented database.

Essential differences between CouchDB and MongoDB

1. The priority of CouchDB is availability, whereas the priority of MongoDB is consistency.
2. CouchDB accepts queries through a RESTful HTTP API, whereas MongoDB accepts queries using its query language.
3. Whereas MongoDB has a much larger user base, making finding support and hiring employees for the database easier, CouchDB has a less user base.

Conclusion

Document-oriented databases are potent databases that store vast chunks of data. They also perform data storage operations in no time. MongoDB and CouchDB support both data types: structured data and unstructured data. These databases are used worldwide. If you found