Cassandra and Terracotta are "distributed" and can both store data,
but I think the similarities end there. My understanding of Terracotta
from recently evaluating their improvements to quartz is that their
design goals are more focused on distributed and fault tolerant JVM
resource sharing with pe
The following paper on the Articles and Presentations section of the
Cassandra wiki describes Facebook's inbox search implementation:
http://www.cs.cornell.edu/projects/ladis2009/papers/lakshman-ladis2009.pdf
-Nate
On Wed, Feb 24, 2010 at 4:45 PM, Mohammad Abed wrote:
> Either of these solutions
g problem. By now we have been using
> master slaves model but in near future it seems that we will come across a
> lot of problems.
> By the way I tried to find an article about use cases, pros and cons of each
> NoSQL solution but I could not find a detailed explanation about them.
> Th
The workload you originally described does not sound like a difficult
job for a relational database. Do you have any more information on the
specifics of your access patterns and where you feel that an RDBMS
might fall short?
-Nate
On Tue, Feb 23, 2010 at 11:27 PM, Cemal wrote:
> I was not reall
wrote:
> Hi Nate,
>
> On Wed, Feb 3, 2010 at 12:31 AM, Nathan McCall wrote:
>> Thank you for the benchmarks. What version of Cassandra are you using?
> I am using 0.5 release.
>> I had about 80% performance improvement on single node reads after
>> using a trunk build
elp of the SliceRange, but not on keys afaik, but maybe there is a way?
>
> Thanks Erik
>
>
> On Tue, Feb 2, 2010 at 3:55 PM, Nathan McCall
> wrote:
>>
>> Erik,
>> You can do an inverse with 'reversed=true' in SliceRange as part of
>> the SlicePre
you are going to run into those scenarios then some sort of
>> sharding on the keys is required, afaict
>>
>> cheers,
>> jesse
>>
>> --
>> jesse mcconnell
>> jesse.mcconn...@gmail.com
>>
>>
>>
>> On Tue, Feb 2, 2010 at 16:30, Nathan
Erik,
Sure, you could and depending on the workload, that might be quite
efficient for small pieces of data. However, this also sounds like
something that might be better addressed with the addition of a
SuperColumn on "Sorts" and getting rid of "Data" altogether:
Sorts : {
sort_row_1 : {
If I understand you correctly, I think I have a decent example. I have
a ColumnFamily which models user preferences for a "site" in our
system:
UserPreferences : {
123_EDD43E57589F12032AF73E23A6AF3F47 : {
favorite_color : red,
...
}
}
I structured it this way because we have a lot of
Thank you for the benchmarks. What version of Cassandra are you using?
I had about 80% performance improvement on single node reads after
using a trunk build with the results from
https://issues.apache.org/jira/browse/CASSANDRA-688 (result caching)
and playing around with the configuration. I am no
Agreed that there is not much to go on here in the original question.
I will say that we very recently found a good fit with Solr and
Cassandra in how we deal with a very heavy write volume of news
article data. Cassandra is excellent with write throughput and high
availability, but our search use
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