Abstract
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.
Highlights
NoSQL is the term used to express data stores that do not follow the relational model and do not use SQL (Structured Query Language) as the data query language
The CAP theorem states that little bit inconsistencies are tolerable by distributed databases where partitions are allowed [2]
The main databases that fall in the category of document oriented databases are CouchDB and MongoDB
Summary
NoSQL is the term used to express data stores that do not follow the relational model and do not use SQL (Structured Query Language) as the data query language. Custom Java Script functions are used by MongoDB "mapReduce" command to perform the map, reduce and finalize operations. These functions provide immense flexibility but they are very complex. A JavaScript function that “reduces” to a single object all the values associated with a particular key Finalize It follows the reduce method and modifies the output. We can either output to a collection or return the result inline It specifies the selection criteria using query operators for determining the documents input to the map function. The above example shows the use of map-reduce functions in MongoDB to get aggregated results
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