Main Article Content

Subita kumari


The most famous NoSQL document-oriented databases namely CouchDB and MongoDB have been discussed in this paper. CAP theorem is being discussed for MongoDB and CouchDB. Map-Reduce is a parallel and distributive programming paradigm for processing bulk amount of heterogeneous and unstructured data on clusters of computers. Map-Reduce operation has been implemented in MongoDB and CouchDB. MongoDB uses map-reduce to perform aggregation. CouchDB uses map-reduce for querying and implementing views. The paper also presents major differences and use cases of both the databases. It is found that MongoDB is better-suited document-oriented database for today's web applications than CouchDB.


Download data is not yet available.

Article Details



Chodorow, K. (2013). MongoDB: The Definitive Guide: Powerful and Scalable Data Storage. " O'Reilly Media, Inc.".

Frank, L., Pedersen, R. U., Frank, C. H., & Larsson, N. J. (2014, January). The CAP theorem versus databases with relaxed ACID properties. In Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication (p. 78). ACM.

Anderson, J. C., Lehnardt, J., & Slater, N. (2010). CouchDB: The Definitive Guide: Time to Relax. " O'Reilly Media, Inc.".

Henricsson, R., & Gustafsson, G. (2011). A comparison of performance in MongoDB and CouchDB using a Python interface. Bachelor thesis BTH.

Kumari, S., & Gupta, P. (2017a). Proposed Architecture of MongoDB-Hive Integration. International Journal of Applied Engineering Research, 12(15), 5000-5004.

Kumari, S., & Gupta, P. (2018). Implementation of CouchDBViews. In Big Data Analytics (pp. 241-251). Springer, Singapore.

Gulia, P. & Hemlata (2017). Novel Algorithm for PPDM of Vertically Partitioned Data. International Journal of Applied Engineering Research, 12(12), 3090-3096

Hemlata, Gulia, P. (2018). DCI3 Model for Privacy Preserving in Big Data. In Big Data Analytics (pp. 351-362). Springer, Singapore.