MongoDB and Couchbase Server, both NoSQL document databases, have similar data modeling capabilities despite using BSON and JSON formats, respectively. Their data models can be structured using either embedded or normalized (referred in Couchbase) approaches, allowing for complex documents with nested objects and arrays, or smaller, separate documents that enhance performance and minimize data duplication. While MongoDB uses Collections and ObjectIds for document identification, Couchbase employs meta properties and type identifiers. The key difference lies in querying capabilities; Couchbase facilitates easier data retrieval through N1QL, enabling server-side joins of referred documents, whereas MongoDB requires application-level management of relationships. Overall, transitioning between the two databases is straightforward, as data modeling concepts are largely transferable.