Re: [Bigdata-developers] bigdata 1.0.0 release announcement

[Jack P. <jac...@gm...>]

I suppose if you are speaking of those iomega 4tb boxes as consumer
level, then yes. I maintain a connection with it, but do notice that
it sometimes takes a while to respond.

Jack

On Tue, Jul 5, 2011 at 10:36 AM, Bryan Thompson <br...@sy...> wrote:
> We have people who deploy against NAS.  Or are you speaking about a consumer level device? Those often do not offer a full time connection. Bryan
>
>> -----Original Message-----
>> From: Jack Park [mailto:jac...@gm...]
>> Sent: Tuesday, July 05, 2011 1:32 PM
>> To: big...@li...
>> Subject: Re: [Bigdata-developers] bigdata 1.0.0 release announcement
>>
>> When one chooses the path to the journal, has anyone had any
>> success choosing a path to one of those RAID networked
>> terabyte stores?
>>
>> Jack
>>
>> On Tue, Jul 5, 2011 at 10:26 AM, Bryan Thompson
>> <br...@sy...> wrote:
>> > This is a bigdata (R) release.  This release is capable of
>> loading 1B
>> > triples in under one hour on a 15 node cluster.  JDK 1.6 is
>> required.
>> >
>> > Bigdata(R) is a horizontally scaled open source architecture for
>> > indexed data with an emphasis on semantic web data architectures.
>> > Bigdata operates in both a single machine mode (Journal)
>> and a cluster
>> > mode (Federation).  The Journal provides fast scalable ACID indexed
>> > storage for very large data sets.  The federation provides fast
>> > scalable shard-wise parallel indexed storage using dynamic sharding
>> > and shard-wise ACID updates.  Both platforms support fully
>> concurrent readers with snapshot isolation.
>> >
>> > Distributed processing offers greater throughput but does
>> not reduce
>> > query or update latency.  Choose the Journal when the anticipated
>> > scale and throughput requirements permit.  Choose the
>> Federation when
>> > the administrative and machine overhead associated with operating a
>> > cluster is an acceptable tradeoff to have essentially
>> unlimited data scaling and throughput.
>> >
>> > See [1,2,8] for instructions on installing bigdata(R), [4] for the
>> > javadoc, and [3,5,6] for news, questions, and the latest
>> developments.
>> > For more information about SYSTAP, LLC and bigdata, see [7].
>> >
>> > Starting with this release, we offer a WAR artifact [8] for easy
>> > installation of the Journal mode database.  For custom
>> development and
>> > cluster installations we recommend checking out the code from SVN
>> > using the tag for this release.  The code will build automatically
>> > under eclipse.  You can also build the code using the ant
>> script.  The
>> > cluster installer requires the use of the ant script.  You
>> can checkout this release from the following URL:
>> >
>> >
>> https://bigdata.svn.sourceforge.net/svnroot/bigdata/branches/BIGDATA_R
>> > ELEASE_1_0_0
>> >
>> > New features:
>> >
>> > - Single machine data storage to ~50B triples/quads (RWStore);
>> > - Simple embedded and/or webapp deployment (NanoSparqlServer);
>> > - Fast 100% native SPARQL 1.0 evaluation with lots of query
>> > optimizations;
>> >
>> > Feature summary:
>> >
>> > - Triples, quads, or triples with provenance (SIDs);
>> > - Fast RDFS+ inference and truth maintenance;
>> > - Clustered data storage is essentially unlimited;
>> > - Fast statement level provenance mode (SIDs).
>> >
>> > The road map [3] for the next releases includes:
>> >
>> > - High-volume analytic query and SPARQL 1.1 query, including
>> > aggregations;
>> > - Simplified deployment, configuration, and administration for
>> > clusters; and
>> > - High availability for the journal and the cluster.
>> >
>> > For more information, please see the following links:
>> >
>> > [1]
>> >
>> https://sourceforge.net/apps/mediawiki/bigdata/index.php?title=Main_Pa
>> > ge [2]
>> >
>> https://sourceforge.net/apps/mediawiki/bigdata/index.php?title=Getting
>> > Started [3]
>> >
>> https://sourceforge.net/apps/mediawiki/bigdata/index.php?title=Roadmap
>> > [4] http://www.bigdata.com/bigdata/docs/api/
>> > [5] http://sourceforge.net/projects/bigdata/
>> > [6] http://www.bigdata.com/blog
>> > [7] http://www.systap.com/bigdata.htm
>> > [8] https://sourceforge.net/projects/bigdata/files/bigdata/
>> >
>> > About bigdata:
>> >
>> > Bigdata(r) is a horizontally-scaled, general purpose storage and
>> > computing fabric for ordered data (B+Trees), designed to operate on
>> > either a single server or a cluster of commodity hardware.
>> Bigdata(r)
>> > uses dynamically partitioned key-range shards in order to
>> remove any
>> > realistic scaling limits - in principle, bigdata(r) may be
>> deployed on
>> > 10s, 100s, or even thousands of machines and new capacity
>> may be added
>> > incrementally without requiring the full reload of all data. The
>> > bigdata(r) RDF database supports RDFS and OWL Lite
>> reasoning, high-level query (SPARQL), and datum level provenance.
>>
>> --------------------------------------------------------------
>> ----------------
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