CODEWITHSUNDEEP
relational-databasecassandra
RandomUser
RandomUser

Reputation: 4220

Cassandra write performance vs Releational Databases

I am trying to grasp some performance differences between Cassandra and relational databases.

From what I have read, Cassandra's write performance remains constant regardless of data volume. By write performance, I am assuming this implies both new rows being added as well as existing rows being replaced on a key match (like an update in the relational world). Is that assumption correct?

Also, from what I understand about relational databases updates get slower when tables/partitions become larger. This is because a full table scan must be performed to locate the row, or an index lookup needs to be performed and both of these things will take longer as the table or partition grows. So updates take perpetually longer based on the data volume of the table/partition?

When new data is inserted to a relational database, I know any indexes need to to have the new data but there is no lookup involved correct? So will inserts also become perpetually slower as data volume increases or stay constant with relational databases?

Thanks for any tips

Upvotes: 1

Views: 1821

Answers (2)

maasg
maasg

Reputation: 37435

On the relational DB side, I've been doing load testing on our RDBMS where I can see that the performance drops exponentially as data is added to the DB. RDBMS performace test

I'm still working on a Cassandra setup to be able to realize a comparable test. In the meantime, this Cassandra presentation gives some info on Cassandra compared to MySQL: http://www.slideshare.net/Eweaver/cassandra-presentation-at-nosql

Upvotes: 1

GolezTrol
GolezTrol

Reputation: 116170

They will become slower if the table has indexes. Not only the data must be written, but the index must be updated too. Inserting in a table that has no indexes and no constraints is lightning fast, because no checks need to be done. The record can just be written at the end of the table space.

Upvotes: 5

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