Storing RDF data into HBase? - Semantic Overflow. I can't comment specifically on HBase, but I have implemented RDF storage for Cassandra which has a very similar BigTable-inspired data model. You basically have two options in how to store RDF data in wide-column databases like HBase and Cassandra: the resource-centric approach and the statement-centric approach. In the statement-oriented approach, each RDF statement corresponds to a row key (for instance, a UUID) and contains subject, predicate and object columns.
In Cassandra, each of these would be supercolumns that would then contain subcolumns such as type and value, to differentiate between RDF literals, blank nodes and URIs. If you needed to support named graphs, each row could also have a context column that would contain a list of the named graphs that the statement was part of. In view of the previous considerations, the resource-oriented approach is generally a better natural fit for storing RDF data in wide-column databases. How RDF Databases Differ from Other NoSQL Solutions - The Datagr. This started out as an answer at Semantic Overflow on how RDF database systems differ from other currently available NoSQL solutions.
I've here expanded the answer somewhat and added some general-audience context. RDF database systems are the only standardized NoSQL solutions available at the moment, being built on a simple, uniform data model and a powerful, declarative query language. These systems offer data portability and toolchain interoperability among the dozens of competing implementations that are available at present, avoiding any need to bet the farm on a particular product or vendor. In case you're not familiar with the term, NoSQL ("Not only SQL") is a loosely-defined umbrella moniker for describing the new generation of non-relational database systems that have sprung up in the last several years.
These systems tend to be inherently distributed, schema-less, and horizontally scalable. Present-day NoSQL solutions can be broadly categorized into four groups: Pius's rdf-mongo at master - GitHub. RDFgrid - Map/Reduce-based Linked Data Processing with Hadoop. Evri Ties the Knot with Twine — Twine CEO Comments and Analysis. Today I am announcing that my company, Radar Networks, and its flagship product, Twine, have been acquired by Evri. TechCrunch broke the story here. This acquisition consolidates two leading providers of semantic discovery and search. It is also the culmination of a long and challenging venture to pioneer the adoption of the consumer Semantic Web.
As the CEO and founder of Radar Networks and Twine.com, it is difficult to describe what it feels like to have reached this milestone during what has been a tumultuous period of global recession. Selling Twine.com was not something we had planned on doing at this time, but given the economy and the fact that Twine.com is a long-term project that will require significant ongoing investment and work to reach our goals, it is the best decision for the business and our shareholders. The Twine team is joining Evri to continue our work there. It is always an emotional experience to sell a company.
What I’m Doing Next The Story Behind the Story. Evri Acquires Radar Networks In Semantic Search Consolidation. After shopping itself around to all the major search engines, Radar Networks finally found a buyer in another semantic search startup. Today, Evri is announcing that it will be acquiring Radar Networks, along with its core technical team and its main product, Twine. Rumors surfaced yesterday on ReadWriteWeb that Evri was being acquired, but that is not the case. Evri is the acquirer. I spoke with both CEOs this morning. They would not disclose the terms of the deal, but it is safe to assume that it was largely an equity-based transaction.
Evri, on the other hand, has been focusing more on filtering the realtime Web and then creating a semantic index of those pages based on matching similar content. “We had to find a home,” explains Radar CEO Nova Spivack. Semantic search is still in its infancy. RDF::Cassandra - Apache Cassandra Storage Adapter for RDF.rb. This is an RDF.rb plugin that adds support for storing RDF data in the Apache Cassandra distributed database management system.
Features Stores RDF statements in a resource-centric manner using one Cassandra supercolumn family per RDF repository.Inherits Cassandra's characteristics of high availability, eventual consistency, and horizontal scalability.Optimized for write-heavy workloads with no need to perform a read before inserting or deleting an RDF statement.Optimized for resource-oriented access patterns to RDF statements about a particular subject.Partitions RDF data across the Cassandra cluster based on subject URIs, improving data locality when accessing statements about a particular subject.Includes a set of Rake tasks that make it easy to download and setup a local development instance of Cassandra. Limitations Does not support named graphs at present. Examples require 'rdf/cassandra' Connecting to a Cassandra server running on localhost repository = RDF::Cassandra::Repository.new.
'Lost' Possibly Still Airing In Parallel Dimension, Desperate Fa.