81–90 of 99 posts
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It's particularly flawed given: a) IO is such a large portion of the problem b) Hypertable isn't just way, way faster.
"a) IO is such a large portion of the problem" I'm very interested in a cluster benchmark therefor, say 10 servers, as Cassandra claims to scale very well. With a cluster IO has a higher performance impact than one server with local RAID IO.
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It's particularly flawed given: a) IO is such a large portion of the problem b) Hypertable isn't just way, way faster.
Are there any recent comparative benchmarks of hypertable? I looked around but couldn't find any.
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Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure....... There is nothing commodity about a server with 128GB RAM. When you introduce other nodes, you get chatter and network traffic....
Nothing commodity about a server with 128GB RAM? At list price, you can configure one of dell's entry-level servers with 128GB of RAM for less than $3,500. http://www.dell.com/us/business/p/poweredge-rack-servers
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Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure....... There is nothing commodity about a server with 128GB RAM. When you introduce other nodes, you get chatter and network traffic....
Nothing commodity about a server with 128GB RAM? At list price, you can configure one of dell's entry-level servers with 128GB of RAM for less than $3,500. http://www.dell.com/us/business/p/poweredge-rack-servers
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http://www.scylladb.com/technology/memory/ By the way, I think you're replying to one of the devs of Scylla.
So, in general, I understand there is lots of stuff going on in Scylla that does distinguish it, at least from Cassandra. There is the user space networking logic for IO. However, a lot of the IO overhead with disk, for example.
That's why they benchmarked this workload on a 4x SSD RAID configuration :). Given that i/o bandwidth and throughput continues to increase, processor frequency isn't, and core counts are going up, it's prudent to design a system that can take advantage of this.
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So, in general, I understand there is lots of stuff going on in Scylla that does distinguish it, at least from Cassandra. There is the user space networking logic for IO. However, a lot of the IO overhead with disk, for example.
>However, a lot of the IO overhead with disk, for example. That's why they benchmarked this workload on a 4x SSD RAID configuration :). Given that i/o bandwidth and throughput continues to increase, processor frequency isn't, and core counts are going up, it's prudent to design a system that can take advantage of this.
I'm sure there is a way to set up IO subsystems so that Cassandra becomes a huge bottleneck, but that's a pretty specialized context.
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http://www.scylladb.com/technology/cassandra-vs-scylla-laten...
> The test hardware configuration includes: > 1 DB server (Cassandra / Scylla) The whole point of Cassandra is to run a cluster of servers to handle load at scale with minimal friction instead of having to buy a big single machine or spend all your time/money trying to run a clustered RDBMS. This test doesn't measure the correct thing.
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Agreed, but which architectural features are you referring to?
Over the last decade, the distributed system nature of modern server hardware internals has become painfully evident in how software architectures scale on a single machine. The traditional approaches -- multithreading, locking, lock-free structures, etc -- are all forms of coordination and agreement in a distributed system, with the attendant scalability problems if not used very carefully. At some point several yea…
I have no idea how to do any of these things. What are the system/api calls to lock a process to a kernel? How do you bypass kernel IO?
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I really appreciate your insight, but I didn't understand why you keep implying "open source" as some kind of lack-behind design?
In practice, open source databases use more traditional, simpler architectures for which there is a lot of literature. Ironically, you see a lot more creativity and experimentation in closed source database architectures, and this has accrued some substantial benefits to those implementations. The architecture at the link looks unusual compared to open source databases but it is actually a common architecture pattern…
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Over the last decade, the distributed system nature of modern server hardware internals has become painfully evident in how software architectures scale on a single machine. The traditional approaches -- multithreading, locking, lock-free structures, etc -- are all forms of coordination and agreement in a distributed system, with the attendant scalability problems if not used very carefully. At some point several yea…
I think that's a generalization that simply shifts the burden elsewhere, and cannot be said to be "the right" architecture in general. There is a reason CPUs implement cache-coherence on top of their "innate" shared-nothing design, and the reason is abstraction. If you don't need certain abstractions, then a sharded approach is indeed optimal, but if you do, then you have to implement them at some level or another, a…
And yes, you can write high performance Java, but for whatever reasons the Cassandra codebase isn't an example of that. They just did a big storage engine rewrite and the result is slower.