Various performance facets

Other than the JavaScript-friendly nature, one other resemblance between MongoDB and Node.js is that MongoDB is also designed with highly concurrent applications with heavy read operations in mind.

MongoDB also introduces the concept of sharding, which makes it possible to scale the database horizontally as well as vertically. If the application owner needs to increase the database capabilities, they could add more machines into the stack. This is a cheaper option compared to investing in the RAM of a single machine, which will be the case in RDBMS solutions.

The process of Indexing created a list of values called index for a chosen field. These indexes are used to query larger chunks of data. Using indexes accelerates the data retrieval speed and performance. The MongoDB client provides various methods like ensureIndex to create an index only if one doesn't exist.

Additionally, MongoDB has various commands to allow aggregation of data, such as group, count, and return distinct values.

All the advantages that we discussed come with some impact on the consistency, as MongoDB does not strictly adhere to the RDBMS standards like ACID transactions. Also, if you end up creating a data model that might need too many JOIN operations, then MongoDB won't make a good fit as it is not designed with too many aggregations, even though the aggregations are possible via the MongoDB aggregation framework. MongoDB may or may not be the right solution for your application. You should truly weigh the pros and cons of each technology before making a decision to determine which technology is right for you.