MySQL vs. MongoDB Read Performance: When Does Relational Outperform Document Databases?

MySQL and MongoDB: Performance Comparison for Read Operations

In a quest for performance optimization, you have conducted a thorough comparison between MySQL and MongoDB, two popular database systems. Despite your expectations, the results were surprising. MySQL's performance was comparable to MongoDB's in a scenario involving random read operations on a large dataset.

Examining the Results

The key to understanding the outcome lies in the similarities between the data organization and query patterns used in both databases. MongoDB's supposed superiority is derived from its ability to accommodate data models that differ significantly from traditional relational structures.

Relational Data vs. Document Data

In your experiment, the MySQL table followed a relational model, with rows representing individual records and columns representing attributes. MongoDB's collection, on the other hand, operated on a document-based model, where documents encapsulated the entire data for an entity.

Implications for Read Performance

To retrieve a complete entity from a relational database like MySQL, multiple index lookups and data retrievals are typically required, each involving separate tables. In this case, MySQL's reliance on multiple indexes and fragmented data distribution (due to normalization) resulted in approximately 20 times more I/O operations.

MongoDB's Advantage

In contrast, MongoDB's schema flexibility allowed you to model the entity data as a single document within a collection. This enabled you to access the entire entity with a single index lookup and a single page retrieval, minimizing the number of I/O operations significantly.

Conclusion

While MongoDB can indeed deliver superior performance in certain scenarios, your experience demonstrates that it is not inherently faster in all cases. The key factor is the data organization and query pattern. If your data fits well within a relational model and your queries follow similar patterns, MySQL's optimized I/O performance and mature ecosystem can match or even outperform a document database like MongoDB.

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