High volume data series storage and queries

Alexander Sicular siculars at gmail.com
Tue Aug 9 12:03:24 EDT 2011


If you want to stay nosql, look at Cassandra. I'm not certain about its on
disk overhead though. But I'm pretty sure it is more favorable towards
smaller values.

Also, to qualify my last post, if you do batch insert your values every
minute or so you may not be working with small values anymore. Then the
overhead becomes less of a concern.

-Alexander

Sent from my rotary phone.
On Aug 9, 2011 11:25 AM, "Les Mikesell" <lesmikesell at gmail.com> wrote:
> On 8/9/2011 10:14 AM, Jeremiah Peschka wrote:
>> Excellent points, Alex.
>>
>> When you compare Riak's storage overhead to something like an RDBMS where
you have maybe 24 bytes for row overhead (as is the case for PostgreSQL),
you'll find that there's a tremendous economy of space elsewhere.
>>
>> Riak is going to excel in applications where reads and writes will be
truly random. Yes, there are Map Reduce features, but randomly organized
data is still randomly organized data.
>>
>> If you look at RDBMSes, horizontally partitioning your system through
RDBMS features (SQL Server's partitioned tables, PostgreSQL's partitioned
views, for example), gives you the ability to take advantage of many known
quantities in that world - range queries can take advantage of sequential
scan speeds across rotational disks.
>
> Do any of the 'other' tools that might be better at handling small or
> naturally-ordered bits of data match riak's ability to scale up and down
> or handle schema changes without a lot of human intervention?
>
> --
> Les Mikesell
> lesmikesell at gmail.com
>
>
>
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