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MongoDB vs SQL

By Priya PedamkarPriya Pedamkar

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.

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Hadoop, Data Science, Statistics & others

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

Interest on DB Engines

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

MongoDB usage

Head to Head Comparison Between MongoDB and SQL

Below is the top 7 difference between MongoDB and SQL:

MongoDB vs SQL Infographics

Key Differences Between MongoDB and SQL

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 and SQL Comparison Table

The primary comparison between MongoDB and SQL are discussed below.

Basis of Comparison Between MongoDB vs SQL

 SQL

MongoDB
Definition SQL or structured query language is a domain specific language used in programming and designed for managing data held in a Relational Database Management System (RDBMS). It is particularly useful in handling structured data where there are relations between different entities/variables of the data. 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.
About Designed by Donald.D.Chamberlin and Raymond Boyce and first appeared in 1974. Developed by MongoDB Inc. and first released in the year 2009, MongoDB is primarily written in C++, C and Java Script.
Terminology and Concepts Comparison
  1. Database
  2. Table
  3. Row
  4. Column
  5. Index
  6. Table Joins
  7. Primary Key-Specify any unique column or column combination as a primary key.
  8. Aggregation(Group by)
  9. Transactions
  1. Database
  2. Collection
  3. Document or BSON document
  4. Field
  5. Index
  6. $lookup, embedded documents
  7. Primary key-In MongoDB the primary key is automatically set to the id field.
  8. Aggregation Pipeline
  9. Transactions
Features
  • High Performance
  • High Availability
  • Scalability and Flexibility
  • Robust Transactional support.
  • High Security
  • Comprehensive Application Development
  • Management Ease
  •  Open Source
  • Support ad hoc queries
  • Indexing
  • Replication
  • Duplication of Data
  • Load balancing
  • Supports map-reduce and aggregation tools
  • Uses JavaScript instead of procedures
  • It is a schema-less database written in C++
  • Provides high performance
  • Stores files of any size easily without complicating your stack
  • Easy to administer in the case of failures
  • It also supports JSON data model, Auto-Sharding and built-in replication.
Best Used for
  • Data Structure fits for tables and rows.
  • Strong dependence on multi-row transactions.
  • Frequent updates and modifications of large volumes of records
  • Relatively small datasets.
  • High write loads
  • Unstable schema
  • When the database is set to grow big
  • Data is location-based
  • High availability in an unstable environment is required
  • When there are no database administrators.
Latest Version 8.0.11 4.0.0
Domains Used In Aerospace and defence, Government, Media and entertainment, Technology and hardware, Telecom, Web games, Education, Healthcare and pharma, Retail, Technology: Open source projects, Travel and hospitality, Web: SAAS, Hosting, Financial services, Manufacturing, Small and medium business, Technology: Software, Web: Ecommerce, Web: Social Networks. Financial Services, Government, Retail, High Tech, Media and Entertainment, Healthcare, Telecommunications1

Conclusion

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.

Recommended Articles

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

  1. MongoDB vs Hadoop differences
  2. MongoDB vs PostgreSQL
  3. MySQL vs NoSQL useful comparisons
  4. Oracle vs PostgreSQL
  5. MySQL vs MongoDB: Features
  6. Guide to MongoDB vs Elasticsearch
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