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DBMS > Badger vs. GraphDB vs. RDF4J vs. Spark SQL

System Properties Comparison Badger vs. GraphDB vs. RDF4J vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Enterprise RDF and graph database with efficient reasoning, cluster and external index synchronization supportRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeGraph DBMS
RDF store
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#291  Overall
#46  Key-value stores
Score1.16
Rank#139  Overall
#8  Graph DBMS
#5  RDF stores
Score0.42
Rank#220  Overall
#9  RDF stores
Score16.93
Rank#35  Overall
#21  Relational DBMS
Websitegithub.com/­dgraph-io/­badgergraphdb.ontotext.comrdf4j.orgspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgergraphdb.ontotext.com/­documentationdocs.rdf4j.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsOntotextSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release2017200020042014
Current release8.8, January 20192.4.5, February 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freeOpen Source infoEclipse Distribution License (EDL), v1.0.Open 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.nono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VM
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-free and OWL/RDFS-schema supportyes infoRDF Schemasyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesno
SQL infoSupport of SQLnoSPARQL is used as query languagenoSQL-like DML and DDL statements
APIs and other access methodsGeoSPARQL
Java API
RDF4J API
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesGo.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Server Pluginyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMaster-master replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)
Foreign keys infoReferential integritynoyes infoConstraint checkingno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyesnono
More information provided by the system vendor
BadgerGraphDB infoformer name: OWLIMRDF4J infoformerly known as SesameSpark SQL
Specific characteristicsGraphDB Enterprise is a high-performance semantic repository created by Ontotext....
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata 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 modelsGraphDB-Free is free to use. SE and Enterprise are licensed per CPU-Core used. Perpetual...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
BadgerGraphDB infoformer name: OWLIMRDF4J infoformerly known as SesameSpark SQL
Conferences and events

GraphDB 9.1: Knowledge Graphs with Data Provenance
Webinar, 2 March 2020 (finished)

GraphDB Fundamentals: Adding Meaning to Your Data
Webinar, 4pm GMT, 8am PST, 5pm CET, 25 March 2020 (finished)

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