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Paper Title (Use Style: Paper Title) 1st National Conference on New Approaches in Electrical and Computer Engineering(NAECE2016) th May.12-13 2016–Islamic Azad University Of Khorram Abad Branch Graph Based NoSQL DataBases : Abilities and Applications Parisa Delfani (Author) Parastou Alavi (Author) Lorestan University ,Khorramabad,Iran Lorestan University ,Khorrramabad,Iran [email protected] Ehsan Azizi Khadem(Author) Lorestan University, Khorramabad, Iran, [email protected] Abstract —Most graph databases are NoSQL in nature and store Graph databases are based on graph theory. Graph databases their data in a key-value store or document-oriented databases. In general terms, they can be considered to be key-value databases employ nodes, properties, and edges. with the additional relationship concept added. Relationships allow the values in the store to be related to each other in a free form Nodes represent entities such as people, businesses, way, as opposed to traditional relational databases where the accounts, or any other item you might want to keep track relationships are defined within the data itself. These relationships of. allow complex hierarchies to be quickly traversed, addressing one of the more common performance problems found in traditional Properties are pertinent information that relate to nodes. key-value stores. Most graph databases also add the concept For instance, if Wikipedia were one of the nodes, one might of tags or properties, which are essentially relationships lacking a have it tied to properties such as website, reference pointer to another document. In computing, a graph database is material, or word that starts with the letter w, depending on a database that uses graph structures for semantic queries with which aspects of Wikipedia are pertinent to the particular nodes, edges and properties to represent and store data. In this database. article, we define the graph databases neo4j, graphdb, Sesame, AllegroGraph , dex first, then we compare the features of each Edges are the lines that connect nodes to nodes, or together.(Abstract) nodes to properties and they represent the relationship between the two. Most of the important information is stored in the edges. Meaningful patterns emerge when INTRODUCTION examining the connections and interconnections of nodes, properties, and edges. Compared with relational databases, graph databases are often faster for associative data sets and map more directly to the AllegroGraph: structure of object-oriented applications. They can scale more AllegroGraph is a graph database built around the W3C spec naturally to large data sets as they do not typically require for the Resource Description Framework. It’s designed for expensive join operations. As they depend less on a rigid handling Linked Data and the Semantic Web, subjects we’ve schema, they are more suitable to manage ad hoc and changing written about often. It supports SPARQL, RDFS++, and Prolog. data with evolving schemas. Conversely, relational databases are AllegroGraph is a proprietary product of Franz Inc., which typically faster at performing the same operation on large markets a number of Semantic Web products – including its numbers of data elements. flagship set of LISP-based development tools. The companyclaims Pfizer, Ford, Kodak, NASA and the Department Graph databases are a powerful tool for graph-like queries, for of Defense among its AllegroGraph customers. example computing the shortest path between two nodes in the graph. Other graph-like queries can be performed over a graph database in a natural way (for example graph's diameter computations or community detection). 1 1st National Conference on New Approaches in Electrical and Computer Engineering(NAECE2016) th May.12-13 2016–Islamic Azad University Of Khorram Abad Branch “Find whether the most important friend of Sonya (using the Name AllegroGraph SNA centrality statistic) made a payment within a 100 miles of Description High performance, Rotterdam, NY (using geospatial) within the last 10 years persistent RDF store with (temporal).” additional support for This would be impossible in any other graph database, RDF Graph DBMS store, document store or Hadoop like solution in such a concise way. AllegroGraph - Combines Geospatial, Temporal, Developer Franz Inc. and SNA into a single “Golden” query. Initial release 2004 Database as aService(DBaaS) No W3C standards based query language and data format Data scheme Yes via SPARQL and RDF. APIs and other access methods RESTful HTTP API SPARQL GRUFF - Data explorer, Graph Visualization, Supportedprogramminglanguages C#, Clojure, Java, Lisp, Graphical Query Generation Perl, Python, Ruby, Scala AllegroGraph has a built-in Rule Based System on top Triggers Yes of an ISO compliant Prolog. Users can write rules and In-memory capabilities No stored procedures in Prolog and make them available to Durability Yes other rules and/or users. User concepts Users with fine-grained authorization concept, Triple Level Security user roles and pluggable authentication True Durability in AllegroGraph - Many RDF and Table-1: Noted Features of AllegroGraph Graph DBMS systems to NOT write transaction logs for every transaciton, so in essence these databases are NOT durable. Specific characteristics: Experiment - Perform multiple commits per second and run AllegroGraph is 100 percent ACID, supporting monitor "vmstat 1" to look at blocks in and out (column - io Transactions: Commit, Rollback, and Checkpointing. Triple Level Security with Security Filters. Gruff - Graph bi/bo). Visualization, Generate SPARQL and Prolog queries visually. System Properties Comparison AllegroGraph vs. GraphDB AllegroGraph server can be scripted using the JavaScript API. Full and Fast Recoverability. 100% Read Concurrency, Near Full Write Concurrency. Online Backups, Point-in-Time Name AllegroGraph GraphDB Recovery, Replication, Warm Standby. Dynamic and Automatic Description High Graph database and RDF Indexing – All committed triples are always indexed (7 indices). Advanced Text Indexing – Text indexing per predicate. performance, triplestore built on OWL SOLR and MongoDB Integration. SPIN support (SPARQL persistent RDF standards Inferencing Notation). The SPIN API allows you to define a function in terms of a SPARQL query and then call that function store with in other SPARQL queries. These SPIN functions can appear in additional FILTERs and can also be used to compute values in assignment and select expressions. support for Graph DBMS Competitive advantages: AllegroGraph is uniquely suited to support adhoc queries Database model Graph DBMS Graph DBMS through SPARQL, Prolog and languages like JavaScript. AllegroGraph uses sorted quintuple indices that will index every RDF store RDF store primary and non-primary field. So users never have to worry Developer Franz Inc. Ontotext about whether a certain field is indexed or not. There are 6 default indices that are in general sufficient for set based query Initial release 2004 2000 index to execute almost any adhoc query. Database as a No No One of the most powerful features of AllegroGraph is that it is possible to mix Geospatial, Temporal, Social Network Service (DBaaS) Analytics, and Reasoning, all in the same query (SPARQL or Implementation Java Prolog). An example: 2 1st National Conference on New Approaches in Electrical and Computer Engineering(NAECE2016) th May.12-13 2016–Islamic Azad University Of Khorram Abad Branch Developer Franz Inc. Aduna language Server operating Linux Linux Server operating Linux All OS with a Java VM systems OS X OS X systems OS X Linux Windows Unix Windows OS X Windows Windows Data scheme yes yes Server-side yes Java Server Plugin XML support no scripts Secondary indexes yes Yes Partitioning with Federation None APIs and other RESTful HTTP API Java API methods access methods SPARQL RIO Replication Master-slave Master-master replication Sail API methods replication SeRQL Consistency Immediate Eventual Consistency, Local Sesame REST HTTP concepts Consistency or consistency configurable in High Protocol Eventual Availability Cluster setup SPARQL Consistency SQL No No depending on Partitioning with Federation None configuration methods Triggers Yes No Replication Master-slave replication None Market metrics GraphDB is the most utilized methods semantic triplestore for mission critical enterprise... Consistency Immediate Consistency Key customers BBC, Press Association, concepts or Eventual Consistency Financial Times, DK, Euromoney, AstraZeneca, The depending on British... Licensing and GraphDB-Free is free to use. SE configuration pricing models and Enterprise are license per CPU-Core used. Perpetual,... Transaction ACID ACID Table-2: Compare the features of two Graph Database concepts System Properties Comparison AllegroGraph vs. Sesame User concepts Users with fine-grained No authorization concept, Name AllegroGraph Sesame user roles and pluggable Description High performance, Sesame is a framework for authentication persistent RDF store processing RDF data, Specific AllegroGraph is 100 characteristics percent ACID , with additional support supporting both memory- supporting Transactions: Commit, Rollback, for Graph DBMS based and a disk-based and... Competitive storage. advantages AllegroGraph is Database model Graph DBMS RDF store uniquely suited to RDF store support adhoc queries 3 1st National Conference on New Approaches in Electrical and Computer Engineering(NAECE2016) th May.12-13 2016–Islamic Azad University Of Khorram Abad Branch scenarios Data Management Identity
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