MongoDB vs SQL

Differences Between MongoDB vs SQL

In today’s world driven by modern enterprises, businesses are constantly finding ways to manage or store their data. This could be to gain customer insights, to gain an understanding of the changing user expectations or to beat competitors with new applications and models. This resulted in changes in the earlier assumptions of relational databases. The main drivers being

• Demands for higher developer productivity and faster time to market.
• The need to manage a massive increase in new and rapidly changing data types.
• The wholesale shift to distributed systems and cloud computing.

This gave rise to non-tabular databases like MongoDB. MongoDB is a free and open-source cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with schemas. A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.

1. Interest on DB Engines over time and Movement of Ranking

2.MongoDB usage over weeks from Jan 2013 to Jul 2018

Head to Head Comparison Between MongoDB vs SQL

Below is the top 7 difference between MongoDB vs SQL

Key Differences Between MongoDB vs SQL

Both MongoDB vs SQL are popular choices in the market; let us discuss some of the major Difference Between MongoDB and SQL:

• In MongoDB data is represented as a collection of JSON documents while in MySQL, data is in tables and rows.
• When it comes to querying, we have to put a string in the query language that the DB system parses. The query language is called Structured Query Language. On the other hand, MongoDB’s querying is object-oriented, which means you pass MongoDB a document explaining what you are querying and there is no parsing.
• One big benefit of SQL is the Join statement which allows querying across several tables. MongoDB, on the other hand, does not support JOINS but instead supports multi-dimensional data types like documents and arrays.
• In SQL we can have one document inside another. In MongoDB, we have one array of comments and one collection of posts within a post.
• SQL supports atomic transactions. You can have several operations within a transaction and you can roll back as if you have a single operation. There is no support for transactions in MongoDB and the single operation is atomic.
• In MongoDB, we need not define the schema. We can just drop in the documents. In the case of SQL, we need to define the tables and columns before storage.
• There are no reporting tools with MongoDB i.e. performance testing and analysis is not always possible. In SQL we get several reporting tools.

MongoDB vs SQL Comparison Table

The primary Comparison between MongoDB vs SQL are discussed below:

Conclusion – MongoDB vs SQL

When in a dilemma as to whether to opt for MongoDB or SQL, companies need to keep in mind their data volume and needs. SQL is more apt for smaller datasets whereas MongoDB is capable of handling large unstructured datasets. SQL is recognized for its high performance, flexibility, reliable data protection, high availability, and management ease. MongoDB is, on the other hand, is a go-to solution because of its open and simple philosophy and collaborative and helpful community. In the event that your data is unstructured, complex, there is no pre-determined schema and you need to handle large amounts of data and store it as documents, MongoDB can be preferred over SQL.

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This has a been a guide to the top difference between MongoDB and SQL. Here we also discuss the MongoDB vs SQL key differences with infographics, and comparison table. You may also have a look at the following MongoDB vs SQL articles to learn more –

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