Cassandra is much slower than Mysql for simple operations?

Question

I see a lot of statements like: "Cassandra very fast on writes", "Cassandra has reads really slower than writes, but much faster than Mysql"

On my windows7 system: I installed Mysql of default configuration. I installed PHP5 of default configuration. I installed Casssandra of default configuration.

Making simple write test on mysql: "INSERT INTO wp_test (id,title) VALUES ('id01','test')" gives me result: 0.0002(s) For 1000 inserts: 0.1106(s)

Making simple same write test on Cassandra: $column_faily->insert('id01',array('title'=>'test')) gives me result of: 0.005(s) For 1000 inserts: 1.047(s)

For reads tests i also got that Cassandra is much slower than mysql.

So the question, does this sounds correct that i have 5ms for one write operation on Cassadra? Or something is wrong and should be at least 0.5ms.

Answer 1

When people say "Cassandra is faster than MySQL", they mean when you are dealing with terabytes of data and many simultaneous users. Cassandra (and many distributed NoSQL databases) is optimized for hundreds of simultaneous readers and writers on many nodes, as opposed to MySQL (and other relational DBs) which are optimized to be really fast on a single node, but tend to fall to pieces when you try to scale them across multiple nodes. There is a generalization of this trade-off by the way- the absolute fastest disk I/O is plain old UNIX flat files, and many latency-sensitive financial applications use them for that reason.

If you are building the next Facebook, you want something like Cassandra because a single MySQL box is never going to stand up to the punishment of thousands of simultaneous reads and writes, whereas with Cassandra you can scale out to hundreds of data nodes and handle that load easily. See scaling up vs. scaling out.

Another use case is when you need to apply a lot of batch processing power to terabytes or petabytes of data. Cassandra or HBase are great because they are integrated with MapReduce, allowing you to run your processing on the data nodes. With MySQL, you'd need to extract the data and spray it out across a grid of processing nodes, which would consume a lot of network bandwidth and entail a lot of unneeded complication.