Table 4 Document-oriented databases
From: Modeling temporal aspects of sensor data for MongoDB NoSQL database
Name | Data model | Scalability | Description | Who uses it |
|---|---|---|---|---|
MongoDB from http://10gen.com, MongoDB Inc. [38] | JSON-like hierarchical documents with or without schemas, object mapping, BSON | Sharding, replication and persistency | Most popular JSON document store, ACID, MapReduce, primary secondary indexing, eventual consistency, RESTful | Expedia, Bosh, MetLife, Facebook, comcast, sprinklr |
CouchDB from Apache [88] | Native JSON-document store; types: strings, numbers, dates, ordered lists and associative arrays | Multi-master replication, | JavaScript as query language using MapReduce, and HTTP for an API, multi-version concurrency, MapReduce, ACID, eventual consistency | meebo, AirFi Sophos, BBC, npm CANAL+ |
Couchbase from Couchbase, Inc. [89] | Multi-model: key/value store, document-store; JSON documents | Sharding, master-master and master-slave replication | CouchDB based with Memcached-compatible interface, eventual consistency, limited ACID, eventual consistency, RESTful HTTP API | Informatica, Joyent, intel, Wipro, Google, Simba |
RethinkDB [90] | JSON documents with dynamic schemas | Sharding, master-slave replication | Push real-time data; RethinkDB Query Language (ReQL);Hadoop-style MapReduce; primary&secondary indexes; Not ACID | Jive SW, Mediafly, Pristine Platzi, CMUNE, Wise.io |
Cloudant from IBM, Apache [91] | JSON based flexible documents | Sharding, master-master & master-slave replication | CouchDB based; primary and secondry indexes; MapReduce; Eventual Consistency; RESTful HTTP/JSON API | Samsung, IBM, Expedia, DHL, Microsoft, Pearson |