Hi Luca,

Yes, I ONLY need to read/traverse the graph.

I like the idea of 3000 separate graphs because it lets me take advantage
of parallelism. And I'll rarely (if ever) have to run queries across 
multiple graphs.

I have a separate process that runs daily to collect the updated raw data.
For now it takes < 15 minutes to build the graph from scratch so it's 
simple enough,

Alan

On Friday, December 27, 2013 9:23:59 AM UTC-8, Lvc@ wrote:
>
> Hi Alan,
> what are your usage patterns once the database is filled? I mean is it 
> mostly read/traverse on graph?
>
> Lvc@
>
>
> On 20 December 2013 07:01, Alan Miller <[email protected] 
> <javascript:>>wrote:
>
>> I'm just getting started with OrientDB and trying to determine if & how 
>> OrientDB scales for my use case, so any suggestions would be greatly 
>> appreciated.
>>
>> Here's some numbers to frame what I'd be trying to model in the graph.
>>
>>   - I will have approximately 35 billion vertices.
>>   - Each vertex will have 4 properties (2 longs, an int, and 1 string).
>>   - I will only need 2 edge types (a 1:1 and a 1:many relationship).
>>   - I actually don't need a single graph for all 35 billion nodes, I 
>> could get away
>>     with 3000 separate graphs (approx 11 million nodes per graph).
>>     since my application would always be querying 1 of the 3000 areas of 
>> the graph.
>>
>> Sorry I can't divulge more on what I'm modeling.
>>
>> As a test, I generated a small graph (1 of my 3000) and ended up with 
>> with 2 million vertices and 2 million edges which was 1.1GB on disk.
>> As a ballpark figure I estimated my complete data footprint to be approx. 
>> 20TB.
>>
>> Any ideas, general suggestions on architecting such a (large?) 
>> distributed graph?
>>
>> Alan  
>>
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>

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