MongoDB is a document-oriented DBMS, with JSON-like objects comprising the data model, rather than RDBMS tables. MongoDB does not support joins nor transactions. However, it features secondary indexes, an expressive query language,
atomic writes on a per-document level, and fully-consistent reads. MongoDB uses BSON, a binary object format similar to,
but more expressive than JSON.
MongoDB uses dynamic schemas. We can create collections without defining the structure,i.e. the fields or the types of their values, of the documents. You can change the structure of documents simply by adding new fields or deleting existing ones. Documents in a collection need unique set of fields.
MongoDB database stores its data in collections not in tables The collections are the rough equivalent of RDBMS tables.
A collection holds one or more documents, which corresponds to a record or a row in a relational database table, and each document has one or more fields, which corresponds to a column in a relational database table.
As one of the NoSQL database engines, MongoDB is a pretty trendy product at the moment. MongoDB provides for a fairly permissive database experience (compared to that of a relational database). The MongoDB schema is dynamic, which allows you to insert data in a very flexible way.
One of the key use cases for MongoDB is storing unstructured data, such as from sensor arrays.
MongoDB can comfortably chomp away at large data streams, providing a resilient repository.
What you will learn
How to setup your environment of a local mongoDB database
How to create a database in mongoDB
How to create a collection in mongoDB
How to drop a database in mongoDB
How to create a CRUD operations in mongoDB
How interact with mongoDB using python
How to combine collections in MongoDB