, April 10, 2006 8:16 AM
To: Ora Lassila
Cc: public-semweb-lifesci@w3.org
Subject: Re: [BioRDF] Scalability
Ora Lassila wrote:
> what kind of an in-memory database do you use? I have done some
> preliminary experiments with UniProt etc. data with about 2 million
> triples using our OINK b
Ora Lassila wrote:
what kind of an in-memory database do you use? I have done some preliminary
experiments with UniProt etc. data with about 2 million triples using our
OINK browser (built using the Wilbur toolkit). Performance was very
"interactive" (i.e., "snappy", notice my highly precise met
I've embedded answers to your questions below.
Susie
Cutler, Roger (RogerCutler) wrote:
No problem. Getting back to the main subject of the thread, I'm a
little curious whether you've got some Oracle perspective on this issue.
I understand that new Oracle databases are putting RDF into some
l of complex
joins? If so, is there a potential problem here?
-Original Message-
From: Susie Stephens [mailto:[EMAIL PROTECTED]
Sent: Wednesday, April 05, 2006 5:47 PM
To: Cutler, Roger (RogerCutler)
Subject: Re: [BioRDF] Scalability
Roger,
We didn't have a BioRDF call this we
On 4/5/06, Gary Schiltz <[EMAIL PROTECTED]> wrote:
I wonder if RAM is becoming faster/cheaper
> at a sufficiently fast rate to keep up with or outpace the growth of our
> databases of RDF triples - I suspect not.
Ian Foster :
[[
A useful metric for the rate of technological change is the averag
I haven't used it for RDF storage, but the page for SWI-Prolog's
Semantic Web library (www.swi-prolog.org/packages/semweb.html) claims to
have been "actively used with up to 10 million triples, using
approximately 1GB of memory." I wonder if RAM is becoming faster/cheaper
at a sufficiently fa
Matt,
what kind of an in-memory database do you use? I have done some preliminary
experiments with UniProt etc. data with about 2 million triples using our
OINK browser (built using the Wilbur toolkit). Performance was very
"interactive" (i.e., "snappy", notice my highly precise metrics here ;-)
Hi,
We recently implemented RDF-based queries of BioPAX formatted pathway
data (pkb.stanford.edu) and echo the sentiments about query and storage
technologies. In our case, scalability/performance is related to the
complexity of the query and RDF model and less on the parsing and
sending reso
I've had problems with the size of RDF graphs in memory where we are
operating at around 1 million triples for our database; but my
conclusions about scalability are a little different from yours, so I
will add them here:
1) In memory representations of graphs not using a backend store is
On 4/4/06, Cutler, Roger (RogerCutler) <[EMAIL PROTECTED]> wrote:
My feeling is that until there are scalability issues that can be
analysed, it's rather premature to try and solve them. Having said
that -
> 3 - Limit the amount of information that is actually put into RDF to
> some sort of desc
Roger,
I guess I am not similarly worried about data size -- anymore, as some RDF
folks may remember that I was championing a very different syntax for RDF in
the early days of Semantic Web work. As for your suggestions, I have the
following comments:
1 - Doable, for sure. We have built applicat
Hi Roger,
I believe I can provide some comfort for the scalability issue with our
experience with MAGE-ML.
One thing that greatly alleviates the problem is to use compress
writers/readers (Java provides nice ones), for regularly formatted XML
this can compress to 2-10% the original size.
> 3 -
12 matches
Mail list logo
