![]() ![]() The project tested, analysed and compared the performance and RDBMS vs NoSQL: Performance and Scaling Comparison In short, the benefit comes from the design, not some raw speed difference. Here is a little research that explored RDBMS vs NoSQL using MySQL vs Mongo, the conclusions were inline with Reilly's response. Language used to execute is: PHP5 & Google fastest language GO 1.6 _ Speed comparison of RDBMS vs NoSQL for INSERT, SELECT, UPDATE, DELETE executing different number of rows 10,100,1000,10000,100000,1000000 System used for benchmark: DELL cpu i5 4th gen 1.70Ghz * 4 ram 4GB GPU ram 2GB Speed comparison of MySQL & MongoDB in GOLANG1.6 & PHP5 This is how MongoDB can boost performance in some use cases. So for this example, the final tally is about 20 times more IO with MySQL per logical access, compared to MongoDB. These range lookups are likely comprised of random IO - different tables will definitely reside in different spots on disk, and it's possible that different rows in the same range in the same table for an entity might not be contiguous (depending on how the entity has been updated, etc). So the total for mysql, even assuming that all indexes are in memory (which is harder since there are 20 times more of them) is about 20 range lookups.
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