Is MongoDB good for structured data?

As a document database, MongoDB makes it easy for developers to store structured or unstructured data. It uses a JSON-like format to store documents.

When should I use MongoDB instead of SQL?

SQL databases are used to store structured data while NoSQL databases like MongoDB are used to save unstructured data. MongoDB is used to save unstructured data in JSON format. MongoDB does not support advanced analytics and joins like SQL databases support.

Is MongoDB structured or unstructured?

MongoDB database is a type of unstructured database. MongoDB is an open-source database developed by MongoDB, Inc. MongoDB stores data in JSON-like documents that can vary in structure. Related information is stored together for fast query access through the MongoDB query language.

When would you use a document database like MongoDB instead of a relational database like MySQL or postgresql?

In general, MongoDB creates more work (e.g. more CPU cost) for the client server. For example, to join data one has to issue multiple queries and do the join on the client. Even here in 2017 there is less tooling support for MongoDB than there is for relational databases simply because it is newer.

Is MongoDB good for unstructured data?

MongoDB’s document data model is particularly well suited for storing unstructured data. It stores all related data together within a single document, and doesn’t require data to fit neatly into the rigid structure of relational rows and columns. Unstructured data can represent both a challenge and an opportunity.

Which database is good for big data?

NoSQL allows for high-performance, agile processing of information at massive scale. It stores unstructured data across multiple processing nodes, as well as across multiple servers. As such, the NoSQL distributed database infrastructure has been the solution of choice for some of the largest data warehouses.