Cassandra and Voldemort Benchmarked
kreide33 writes "Key/Value storage systems are gaining in popularity, much because of features such as easy scalability and automatic replication. However, there are several to choose from and performance is an important deciding factor. This article compares the performance of two of the most well-known projects, Cassandra and Voldemort, using several different mixes of access types, and compares both throughput and latency."
Their conclusion was that there was "no clear winner". Not surprising. Both of these products are in their early stages of development (Voldemort v0.80.1, Cassandra 0.6.0-beta3) and will certainly work on optimization and performance issues after the product is stable.
I'd like to have seen them run MySQL, PostgreSQL or SQLite through the same tests so we could see how these NoSQL solutions compared.
Did anyone else read this as comparing Cassandra from King's Quest and Voldemort from Harry Potter?
Are there ANY open source key/value stores that support prefix compression?
I kinda wonder why it's not possible to use these projects as backends for mysql and postgres. Seems to me that shouldn't be that hard an exercise.
Or even having these as mountable volumes.
Is a key/value system a database with just one table that has one key field and one non-key field?
Confucius say, "Find worm in apple - bad. Find half a worm - worse."
Until Voldy pulls that whole Avada Kedavra thing...
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A very large company I know is moving from Oracle/MySQL to Voldemort for certain parts of their system. The two they evaluated were Cassandra and Voldemort.
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Key-value storage? That sounds like the ordinary file system to me.
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Try couchdb if you want to select ranges.
Its keys are stored in a heap, so selecting ranges of values is a core use case.
The view system also uses the same mechanism, so by having a cached view you can emit any key you like per record, and grab individual or ranges of values.
Nifty. :-)
I am in a bit of a rush, so I can't netgrep for it myself right now, but I am curious how these new contenders stack up against more established key-value stores such as Berkeley DB and GDBM. Has anyone run the benchmarks?
Please correct me if I got my facts wrong.
You could, but as soon as you try to implement the features of SQL that they lack on top of them you'll end up making them peform far worse than existing backends that are designed from the ground up to provide these features, so what would be the point?