AllegroGraph

Last updated
AllegroGraph
Developer(s) Franz Inc.
Stable release
7.3.1 / December 20, 2022;17 months ago (2022-12-20)
Repository
Written in Java, Python, Common Lisp
Operating system Microsoft Windows (32 and 64-bit), Mac OS X (Intel, 32 and 64-bit), Linux (32 and 64-bit)
License Proprietary commercial software
Website allegrograph.com

AllegroGraph is a closed source triplestore which is designed to store RDF triples, a standard format for Linked Data. [1] It also operates as a document store designed for storing, retrieving and managing document-oriented information, in JSON-LD format. AllegroGraph is currently in use in commercial projects [2] [3] [4] [5] and a US Department of Defense project. [6] It is also the storage component for the TwitLogic project [7] that is bringing the Semantic Web to Twitter data. [8]

Contents

Implementation

AllegroGraph was developed to meet W3C standards for the Resource Description Framework, so it is properly considered an RDF Database. It is a reference implementation for the SPARQL protocol. [9] SPARQL is a standard query language for linked data, serving the same purposes for RDF databases that SQL serves for relational databases. [10]

Franz Inc. is the developer of AllegroGraph. It also develops Allegro Common Lisp, an implementation of Common Lisp, a dialect of Lisp (programming language). The functionality of AllegroGraph is made available through Java, Python, Common Lisp and other APIs. [11]

The first version of AllegroGraph was made available at the end of 2004. [12]

Languages

AllegroGraph has client interfaces for Java, Python, Ruby, Perl, C#, Clojure, and Common Lisp. The product is available for Windows, Linux, and Mac OS X platforms, supporting 32 or 64 bits. [13]

For query languages, besides SPARQL, AllegroGraph also supports Prolog and JavaScript. [14]

Related Research Articles

<span class="mw-page-title-main">Semantic Web</span> Extension of the Web to facilitate data exchange

The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.

The Resource Description Framework (RDF) is a World Wide Web Consortium (W3C) standard originally designed as a data model for metadata. It has come to be used as a general method for description and exchange of graph data. RDF provides a variety of syntax notations and data serialization formats, with Turtle currently being the most widely used notation.

SPARQL is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format. It was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is recognized as one of the key technologies of the semantic web. On 15 January 2008, SPARQL 1.0 was acknowledged by W3C as an official recommendation, and SPARQL 1.1 in March, 2013.

A semantic wiki is a wiki that has an underlying model of the knowledge described in its pages. Regular, or syntactic, wikis have structured text and untyped hyperlinks. Semantic wikis, on the other hand, provide the ability to capture or identify information about the data within pages, and the relationships between pages, in ways that can be queried or exported like a database through semantic queries.

<span class="mw-page-title-main">RDFLib</span> Python library to serialize, parse and process RDF data

RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form. The library also contains both in-memory and persistent Graph back-ends for storing RDF information and numerous convenience functions for declaring graph namespaces, lodging SPARQL queries and so on. It is in continuous development with the most recent stable release, rdflib 6.1.1 having been released on 20 December 2021. It was originally created by Daniel Krech with the first release in November, 2002.

Oracle Spatial and Graph, formerly Oracle Spatial, is a free option component of the Oracle Database. The spatial features in Oracle Spatial and Graph aid users in managing geographic and location-data in a native type within an Oracle database, potentially supporting a wide range of applications — from automated mapping, facilities management, and geographic information systems (AM/FM/GIS), to wireless location services and location-enabled e-business. The graph features in Oracle Spatial and Graph include Oracle Network Data Model (NDM) graphs used in traditional network applications in major transportation, telcos, utilities and energy organizations and RDF semantic graphs used in social networks and social interactions and in linking disparate data sets to address requirements from the research, health sciences, finance, media and intelligence communities.

In computing, Terse RDF Triple Language (Turtle) is a syntax and file format for expressing data in the Resource Description Framework (RDF) data model. Turtle syntax is similar to that of SPARQL, an RDF query language. It is a common data format for storing RDF data, along with N-Triples, JSON-LD and RDF/XML.

An RDF query language is a computer language, specifically a query language for databases, able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.

Ontotext is a software company with offices in Europe and USA. It is the semantic technology branch of Sirma Group. Its main domain of activity is the development of software based on the Semantic Web languages and standards, in particular RDF, OWL and SPARQL. Ontotext is best known for the Ontotext GraphDB semantic graph database engine. Another major business line is the development of enterprise knowledge management and analytics systems that involve big knowledge graphs. Those systems are developed on top of the Ontotext Platform that builds on top of GraphDB capabilities for text mining using big knowledge graphs.

<span class="mw-page-title-main">Apache Jena</span> Open source semantic web framework for Java

Apache Jena is an open source Semantic Web framework for Java. It provides an API to extract data from and write to RDF graphs. The graphs are represented as an abstract "model". A model can be sourced with data from files, databases, URLs or a combination of these. A model can also be queried through SPARQL 1.1.

<span class="mw-page-title-main">RDF4J</span>

Eclipse RDF4J is an open-source framework for storing, querying, and analysing RDF data. It was created by the Dutch software company Aduna as part of "On-To-Knowledge", a semantic web project that ran from 1999 to 2002. It contains implementations of an in-memory triplestore and an on-disk triplestore, along with two separate Servlet packages that can be used to manage and provide access to these triplestores, on a permanent server. The RDF4J Rio package contains a simple API for Java-based RDF parsers and writers. Parsers and writers for popular RDF serialisations are distributed along with RDF4J, and users can easily extend the list by putting their parsers and writers on the Java classpath when running their application.

A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description logic language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including non-axiomatic reasoning systems, and probabilistic logic networks.

A triplestore or RDF store is a purpose-built database for the storage and retrieval of triples through semantic queries. A triple is a data entity composed of subject–predicate–object, like "Bob is 35" or "Bob knows Fred".

A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph. The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships between the nodes. The relationships allow data in the store to be linked together directly and, in many cases, retrieved with one operation. Graph databases hold the relationships between data as a priority. Querying relationships is fast because they are perpetually stored in the database. Relationships can be intuitively visualized using graph databases, making them useful for heavily inter-connected data.

GeoSPARQL is a standard for representation and querying of geospatial linked data for the Semantic Web from the Open Geospatial Consortium (OGC). The definition of a small ontology based on well-understood OGC standards is intended to provide a standardized exchange basis for geospatial RDF data which can support both qualitative and quantitative spatial reasoning and querying with the SPARQL database query language.

Semantic queries allow for queries and analytics of associative and contextual nature. Semantic queries enable the retrieval of both explicitly and implicitly derived information based on syntactic, semantic and structural information contained in data. They are designed to deliver precise results or to answer more fuzzy and wide open questions through pattern matching and digital reasoning.

Shapes Constraint Language (SHACL) is a World Wide Web Consortium (W3C) standard language for describing Resource Description Framework (RDF) graphs. SHACL has been designed to enhance the semantic and technical interoperability layers of ontologies expressed as RDF graphs.

NitrosBase is a Russian high-performance multi-model database system. The database system supports relational, graph and document database models.

<span class="mw-page-title-main">Blazegraph</span> Open source triplestore and graph database

Blazegraph is an open source triplestore and graph database, developed by Systap, which is used in the Wikidata SPARQL endpoint and by other large customers. It is licensed under the GNU GPL.

<span class="mw-page-title-main">Ontotext GraphDB</span> RDF-store

Ontotext GraphDB is a graph database and knowledge discovery tool compliant with RDF and SPARQL and available as a high-availability cluster. Ontotext GraphDB is used in various European research projects.

References

  1. ↑ Claburn, Thomas (16 April 2007). "Web 2.0 Arrives to Find Web 3.0 Underway". Dr. Dobb. UBM Tech. Archived from the original on 4 September 2015. Retrieved 22 September 2015.
  2. ↑ GenomeWeb-Pfizer Article
  3. ↑ Eli Lilly Project Presentation
  4. ↑ "Making a Semantic Web Business Case at Pfizer". Archived from the original on 2010-06-27. Retrieved 2010-05-18.
  5. ↑ Society, IEEE Computer (2008). Proceedings, IEEE International Conference on Semantic Computing 2008 ICSC 2008 : 4-7 August 2008, Santa Clara, California. [Piscataway, N.J.]: IEEE Xplore. ISBN   978-0-7695-3279-0.
  6. ↑ Contributions to a Semantically Based Intelligence Analysis Enterprise Workflow System
  7. ↑ TwitLogic Paper
  8. ↑ Snoek, C.G.M.; Huurnink, B.; Hollink, L.; de Rijke, M.; Schreiber, G.; Worring, M. (August 2007). "Adding Semantics to Detectors for Video Retrieval" (PDF). IEEE Transactions on Multimedia. 9 (5): 975–986. doi:10.1109/TMM.2007.900156. hdl:1871/24469. S2CID   11528628.
  9. ↑ SPARQL Protocol Implementation Report
  10. ↑ R, Angles (2012). 2012 IEEE International Conference on Data Engineering Workshops. Piscataway: IEEE. ISBN   978-1-4673-1640-8.
  11. ↑ Watson, Mark (2009). Scripting intelligence : Web 3.0 information gathering and processing (New ed.). Berkeley, CA: Apress. ISBN   9781430223511.
  12. ↑ Watson, Mark (2009). Scripting intelligence : Web 3.0 information gathering and processing (New ed.). Berkeley, CA: Apress. ISBN   9781430223511.
  13. ↑ "AllegroGraph Client Downloads".
  14. ↑ Fernandes, Diogo; Bernardino, Jorge (2018). "Graph Databases Comparison: AllegroGraph, ArangoDB, InfiniteGraph, Neo4J, and OrientDB" (PDF). Proceedings of the 7th International Conference on Data Science, Technology and Applications. DATA 2018. Porto: SCITEPRESS – Science and Technology Publications, Lda. pp. 373–380. ISBN   978-989-758-318-6.
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