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DBMS > Badger vs. RDF4J vs. SAP SQL Anywhere vs. Spark SQL vs. Splice Machine

System Properties Comparison Badger vs. RDF4J vs. SAP SQL Anywhere vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRDF storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score4.25
Rank#79  Overall
#43  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerrdf4j.orgwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlspark.apache.org/­sqlsplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerrdf4j.org/­documentationhelp.sap.com/­docs/­SAP_SQL_Anywherespark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperDGraph LabsSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SAP infoformerly SybaseApache Software FoundationSplice Machine
Initial release20172004199220142014
Current release17, July 20153.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.commercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaScalaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infoRDF Schemasyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.noyesno
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statementsyes
APIs and other access methodsJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
HTTP API
JDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoJava
PHP
Python
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes, in C/C++, Java, .Net or Perlnoyes infoJava
Triggersnoyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replication infoDatabase mirroringnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoIsolation support depends on the API usedACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
BadgerRDF4J infoformerly known as SesameSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQLSplice Machine
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