It stores data in flexible, JSON-like documents, meaning fields can vary from document to document and data structure can be changed over time and the uniqueness of the _id parameter helps to get or retrieving data easily ,Indexing, queries, application integration and data migration.The relevant technical considerations, such as differences between the relational and document data models and the implications for schema design.MongoDB is a designed for huge query and data storage. Its performance is mainly based on two key value that is design and scale out. MongoDB uses the document as the basic storage unit. In the relational model, the data will be stored in an individual table. In document model, they are saved as one document and its performance is much faster compared to relational query.It also provides ACID properties at the document level as in the case of relational databases.It supports replica sets; in other words, a failover mechanism is automatically handled. If the primary server goes down, the secondary server becomes the primary automatically, without any human intervention.MongoDB can be a cost effective solution because improves flexibility and reduces cost on hardware and storage. If you have an application that performs lots of writes, Mongo isn't a great solution from my humble opinion. As the data size grows, my team has applied TokuMx to speed up Mongo.