Relational databases, and to a degree MySQL, have become the backbone of commercial organizations. Programmers and database developers have been engaged in a tug-of-war, deciding the best place to store and execute the business logic.

Mongo

Here is a quick, nonrigorous comparison between Mysql and MongoDB

Mysql

MySQL is the most popular Open Source Relational SQL Database Management System. MySQL is one of the best RDBMS being used for developing various web-based software applications. MySQL is developed, marketed and supported by MySQL AB, which is a Swedish company.

In Loading the test data: For 10000 entries, loadTestData execution time was 16327 ms. For 1000 records, updateRandomRecord execution time was 31151 ms. For 1000 records, updateRandomRecordKeyd execution time was 1592 ms. By comparing this with NoSQL databases, MongoDB is better due to the reasons:

  • C++
  • Mac OS X and Linux
  • Thread safe & are deployable to Windows
  • Supports Java, Net, PHP connectors.

MongoDB

MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. In simple words you can say that – Mongo DB is a document-oriented database. It is an open source product, developed and supported by a company named 10gen. MongoDB is available under General Public license for free and it is also available under Commercial license for the manufacturer.

For 10000 records, loadTestData execution time is 1912 ms. For 1000 records, updateRandomRecord execution time is 6484 ms. For 1000 records, updateRandomRecordKeyd execution time is 1097 ms. The Quick Takeaways

  • Key’d updates are similar
  • Additions and non-key’d updates on MongoDB are fundamentally speedier.

Some intriguing different components with respect to the B-Tree database

  • Memory use is division of MySQL, which means it’s significantly less demanding to turn up numerous servers
  • Being schemeless, it is significantly less demanding to make and change collections, which will be required clients
  • Development was likewise magnitudes of request quicker on the storage database. This will be additionally expanded in the event that we utilized the local JSON arrange on the application front end.

The main downside I have seen so far:

  • You can perform batch operations with NoSQL database.
  • SQL-type inquiries and data mining turns out to be more troublesome or if nothing else requires diverse arrangements (Map/Reduce)
  • MongoDB supports auto-sharding but does not support the transactions.

 

 

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About The Author

Deependra Kushwah
Deependra kushwah is a member of the fastest growing bloggers community "betechnical", Author, Youtuber, and hardcore Coder. I love writing code in different languages, I also write blogs on tech tutorials, gadgets review and also post some technical videos on youtube on many topics.

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