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DBMS > GRAKN.AI vs. GraphDB vs. JanusGraph

System Properties Comparison GRAKN.AI vs. GraphDB vs. JanusGraph

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Editorial information provided by DB-Engines
NameGRAKN.AI  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparison
DescriptionGrakn is a distributed, hyper-relational database for managing complex data that serves as a knowledge base for cognitive/AI systems.Enterprise RDF and graph database with efficient reasoning, cluster and external index synchronization supportA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017
Primary database modelGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Graph DBMS
RDF store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#256  Overall
#21  Graph DBMS
#120  Relational DBMS
Score1.13
Rank#141  Overall
#8  Graph DBMS
#5  RDF stores
Score1.80
Rank#116  Overall
#6  Graph DBMS
Websitegrakn.aigraphdb.ontotext.comjanusgraph.org
Technical documentationdev.grakn.ai/­docsgraphdb.ontotext.com/­documentationdocs.janusgraph.org
DeveloperGrakn Labs LtdOntotextLinux Foundation; originally developed as Titan by Aurelius
Initial release201620002017
Current release1.5.8, August 20198.8, January 20190.4.0, July 2019
License infoCommercial or Open SourceOpen Source infoGPL Version 3, commercial licenses availablecommercial infolimited edition freeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono infoNamed S4, Ontotext provides a semantic graph database based on GraphDB in the cloud.no
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Windows
All OS with a Java VM
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyes
SQL infoSupport of SQLnoSPARQL is used as query languageno
APIs and other access methodsconsole (shell)
gRPC protocol
Workbase (visualisation software)
GeoSPARQL
Java API
RDF4J API
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresnoJava Server Pluginyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Cassandranoneyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication infoby using CassandraMaster-master replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoby using Apache Kafka and Apache Zookeepernoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infosubstituted by the relationship featureyes infoConstraint checkingyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyes infoat REST API level; other APIs in progressyesUser authentification and security via Rexster Graph Server
More information provided by the system vendor
GRAKN.AIGraphDB infoformer name: OWLIMJanusGraph infosuccessor of Titan
Specific characteristicsGrakn is the knowledge graph to organise complex networks of data and making it queryable,...
» more
GraphDB Enterprise is a high-performance semantic repository created by Ontotext....
» more
Competitive advantagesExpressive and flexible data model: The meta-schema of Grakn allows for modelling...
» more
GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosLife sciences : Grakn makes working with biological data much easier and accelerates...
» more
Metadata enrichment and management, linked open data publishing, semantic inferencing...
» more
Key customersBBC, Press Association, Financial Times, DK, Euromoney, The British Museum, Getty...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsAGPL and Commercial . The commercial license is priced based on cluster resources...
» more
GraphDB-Free is free to use. SE and Enterprise are licensed per CPU-Core used. Perpetual...
» more
News

The New Improved and Open GraphDB
7 November 2019

It Takes Two to Tango: Knowledge Graphs and Text Analysis
5 November 2019

Semantic Technology and the Strive for Drug Safety
21 October 2019

Artificial Intelligence and the Knowledge Graph
10 October 2019

Semantic Technology-based Media Publishing Boosts User Engagement
26 September 2019

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GRAKN.AIGraphDB infoformer name: OWLIMJanusGraph infosuccessor of Titan
Conferences and events

Grakn Cosmos, the universal conference of technologies built using Grakn
London, UK, 6-7 February 2020

Recent citations in the news

GRAKN.AI: How Haikal Pribadi went from being a refugee to building a database for AI systems
26 October 2017, YourStory.com

Get Started With GRAKN.AI
10 March 2017, DZone News

What Is an Ontology?
15 March 2017, DZone News

Kannur-based startup ArticBot bets big on machine learning
28 October 2017, YourStory.com

Oracle launches startup cloud accelerator in Bristol
20 September 2017, Cloud Pro

provided by Google News

GraphQL And The Rise of Universal Data Access
28 October 2019, Forbes

Ontotext GraphDB - Handling Massive Loads, Queries and Inferencing in Real Time.
10 July 2019, KMWorld Magazine

Ontotext GraphDB Named Innovator in Bloor's Graph Database Market Research
11 February 2019, PRNewswire

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Yahoo Finance

Ontotext's GraphDB 8.9 Boosts Semantic Similarity Search
10 April 2019, PRNewswire

provided by Google News

Comcast, FireEye, Numberly Among Winners of 2019 Scylla User Awards
6 November 2019, Yahoo Finance

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

The year of the graph: Getting graphic, going native, reshaping the landscape
8 January 2018, ZDNet

Amazon Neptune review: A scalable graph database for OLTP
13 May 2019, InfoWorld

Benchmarking Graph Analytics Systems: TigerGraph, Neo4j, Neptune, JanusGraph, and ArangoDB
8 May 2019, Database Trends and Applications

provided by Google News

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