|Phone||510 452 2000 x165|
Franz Inc. is an innovative technology company with expert knowledge in developing and deploying Semantic Web solutions. AllegroGraph, Franz’s high-performance, scalable, disk-based RDF Database, provides the solid storage layer for powerful geotemporal reasoning, social network analytics and ontology modeling capabilities for today’s Semantic Technology applications. Franz’s products and services are uniquely positioned to help bring Web 3.0 ideas to reality.
Franz Inc. was founded in early 1984 as a vehicle to produce and sell Macsyma. While that never developed into a business, Franz Inc. did sell Franz Lisp while working on their own Common Lisp implementation. Franz Lisp died out in the 80s as Common Lisp became more popular. Today, they sell Allegro Common Lisp, which is a direct descendant of the Common Lisp they developed in the mid-80s, and a series of products like AllegroCache built on it.
In late 2004, Franz began a development program focused on delivering scalable RDF database technologies for the Semantic Web, also known as Web 3.0. The product, AllegroGraph, is built on many of the highly optimized technologies found in Allegro CL and AllegroCache and was a natural extension for Franz’s technology stack. The current release of AllegroGraph v3.0 incorporates Geospatial, Temporal and Social Networking Analytics libraries as part of what the Company has termed its Activity Recognition package.
In addition to AllegroGraph’s ability to process billions of RDF triples, AllegroGraph also supports SPARQL, Full Text Search, RDFS++, and Prolog reasoning from Java or Common Lisp applications.
Graph Search Using Ontologies and Content IntelligenceAdded: 3/21/13
|Launch Date||March, 2006|
Capable of processing billions of RDF triples, AllegroGraph is a modern, high-performance, persistent, disk-based RDF graph database with support for SPARQL, RDFS++, and Prolog reasoning from Java applications. The new features of version 3.0 form a unified “Activity Recognition” package for flexibly analyzing networks and events in large volumes of structured and unstructured data.