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DBMS > Bangdb vs. MarkLogic vs. RDFox vs. Solr

System Properties Comparison Bangdb vs. MarkLogic vs. RDFox vs. Solr

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonMarkLogic  Xexclude from comparisonRDFox  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphOperational and transactional Enterprise NoSQL databaseHigh performance knowledge graph and semantic reasoning engineA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Graph DBMS
RDF store
Search engine
Secondary database modelsSpatial DBMSRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitebangdb.comwww.marklogic.comwww.oxfordsemantic.techsolr.apache.org
Technical documentationdocs.bangdb.comdocs.marklogic.comdocs.oxfordsemantic.techsolr.apache.org/­resources.html
DeveloperSachin Sinha, BangDBMarkLogic Corp.Oxford Semantic TechnologiesApache Software Foundation
Initial release2012200120172006
Current releaseBangDB 2.0, October 202111.0, December 20226.0, Septermber 20229.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoBSD 3commercial inforestricted free version is availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++C++Java
Server operating systemsLinuxLinux
OS X
Windows
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-free infoSchema can be enforcedyes infoRDF schemasyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes infosupports customizable data types and automatic typing
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.noyesyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL like support with command line toolyes infoSQL92noSolr Parallel SQL Interface
APIs and other access methodsProprietary protocol
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
RESTful HTTP API
SPARQL 1.1
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
Java
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptJava plugins
Triggersyes, Notifications (with Streaming only)yesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesreplication via a shared file systemyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyes, with Range Indexesyesyes
User concepts infoAccess controlyes (enterprise version only)Role-based access control at the document and subdocument levelsRoles, resources, and access typesyes

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BangdbMarkLogicRDFoxSolr
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