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DBMS > Badger vs. RDFox vs. Splice Machine vs. WakandaDB

System Properties Comparison Badger vs. RDFox vs. Splice Machine vs. WakandaDB

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonRDFox  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.High performance knowledge graph and semantic reasoning engineOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelKey-value storeGraph DBMS
RDF store
Relational DBMSObject oriented DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitegithub.com/­dgraph-io/­badgerwww.oxfordsemantic.techsplicemachine.comwakanda.github.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.oxfordsemantic.techsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperDGraph LabsOxford Semantic TechnologiesSplice MachineWakanda SAS
Initial release2017201720142012
Current release6.0, Septermber 20223.1, March 20212.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++JavaC++, JavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyes infoRDF schemasyesyes
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.nono
Secondary indexesnoyes
SQL infoSupport of SQLnonoyesno
APIs and other access methodsRESTful HTTP API
SPARQL 1.1
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesGoC
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresnoyes infoJavayes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonereplication via a shared file systemMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlnoRoles, resources, and access typesAccess rights for users, groups and roles according to SQL-standardyes

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More resources
BadgerRDFoxSplice MachineWakandaDB
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