Relational databases, and to some extent MySQL, have become the backbone of commercial organizations. A tug-of-war is going on between programmers and database developers regarding the best storage & execution place for business logic. However, a study of MongoDB vs MySQL performance will help you make the best choice for your purpose.
To start with, here’s a quick, non-rigorous MongoDB vs MySQL Performance Comparison
MySQL is the most popular Open Source Relational SQL Database Management System. Also, it is one of the best RDBMS being used for developing various web-based software applications. And, a Swedish company MySQL AB develops, markets, and supports MySQL.
In loading the test data, loadTestData took an execution time of 16327 ms for 10000 entries. And, for 1000 records, updateRandomRecord execution time was 31151 ms and updateRandomRecordKeyd execution time was 1592 ms. However, comparing this with NoSQL databases shows that MongoDB is better due to the following reasons:
- Mac OS X and Linux
- Thread safe & are deployable to Windows
- Supports Java, Net, PHP connectors.
MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. In simple words, Mongo DB is a document-oriented database. Basically, it is an open source product, developed and supported by 10gen. Also, MongoDB is available under General Public license for free and under Commercial license for manufacturers.
The loadTestData execution time for 10000 records is 1912 ms. And for 1000 records, updateRandomRecord execution time is 6484 ms and updateRandomRecordKeyd execution time is 1097 ms. Here are a few Quick Takeaways:
- Key’d updates are similar
- Additions and non-key’d updates on MongoDB are speedier.
Some intriguing different components regarding the B-Tree database
- First, memory use is a division of MySQL, which means it’s less demanding to turn up numerous servers
- Second, being schemeless, it is less demanding to make and change collections as clients require
- Third, development was likewise magnitudes of request quicker on the storage database. However, in case of use of the local JSON arrange on the application frontend, this goes through an additional expansion.
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)
- Also, MongoDB supports auto-sharding but does not support the transactions.
To conclude, this comparison of MongoDB vs MySQL is sure to help you make the right decision.
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