MongoDB Interview Questions

When the mongoose is created at the first time the version key is a property set on every document. The value of this key comprises of the internal revision of the document. It is understood that the name of this document is configurable. The default key is __v

• C
• C++
• C#
• Java
• Node.js
• Perl
• PHP
• Python
• Ruby
• Scala
• Go
• Erlang.

Currently, MongoDB provides driver support for the languages listed above. It can be used easily with any of these languages.

	
		Db.createCollection (name, options)
	

Dropping a collection basically means deleting a collection. Following is the syntax for dropping a collection in MongoDB-

Db.collection.drop()

In MongoDB, a namespace is a combination of the database name and collection or index name. It is a canonical name for an index or a collection in MongoDB. A namespace consists of all the documents in MongoDB. The maximum length of a collection of namespaces is called the namespace length. It consists of the database name, a dot operator (.), and the name of the collection.

Syntax- <database>.<collection>

The namespace contains all the helper classes which can be used to construct various options which are to be used in the drivers. A namespace can also be termed as the concatenation of the collection name and the database name.

1. Aggregation framework– it uses aggregation framework for the batch processing of data and aggregation operations. It should be used in an effective manner.
2. The usage of BSON format in MongoDB– it uses the binary-encoded serialization of JSON-like documents. The data-types like- date and binary are supported in the format.
3. The sharing feature of MongoDB– using this feature, MongoDB supports the distribution of data across multiple machines. It supports deployment with large sets of data.
4. The Ad hoc queries in MongoDB– it supports field, range queries, and regular expressions.
5. Collections– MongoDB supports fixed size collection which can also be termed as capped collections.

• Key value store NoSQL database
• Document store NoSQL database
• Column store NoSQL database
• Graph-based NoSQL database

The various examples of NoSQL database are- MongoDB, Cassandra, CouchDB, Hypertable, Redis, Riak, Neo4j, HBase, Couchbase, MemcacheDB, Voldemort, RevenDB, etc.

• In terms of data representation– in MySQL, we represent data in the form of tables and rows. Whereas, in MongoDB data is represented as collections of JSON documents.
• Querying– in SQL, we put together a string in the query language which is then parsed by the database system. Whereas, in MongoDB, object querying is used.
• Relationships– in MySQL, the relational database is only the Join operation which allows us to perform queries across multiple tables. Whereas MongoDB does not support join operation but can support multi-dimensional data types such as arrays, etc. in this, embedding is a process in which we place one document inside the other.
• Transactions– MySQL supports atomic transactions which are the ability to contain multiple operations within a transaction. Whereas, MongoDB does not support transactions.
• Schema definition– in MySQL, you need to define your tables and columns before storing anything. Whereas, in MongoDB, you don’t need to define a schema.

• Your schema should be designed according to your requirements.
• If the objects are to be used together, you should combine them into one document. Otherwise, you should use them separately.
• Joins should be performed while writing and not while reading.
• If use cases are used more frequently, then you should optimize your schema.
• Complex aggregation should be done in the schema.