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DBMS > Hive vs. MonetDB vs. NSDb vs. RDFox

System Properties Comparison Hive vs. MonetDB vs. NSDb vs. RDFox

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMonetDB  Xexclude from comparisonNSDb  Xexclude from comparisonRDFox  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA relational database management system that stores data in columnsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSRelational DBMSTime Series DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitehive.apache.orgwww.monetdb.orgnsdb.iowww.oxfordsemantic.tech
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.monetdb.org/­Documentationnsdb.io/­Architecturedocs.oxfordsemantic.tech
DeveloperApache Software Foundation infoinitially developed by FacebookMonetDB BVOxford Semantic Technologies
Initial release2012200420172017
Current release3.1.3, April 2022Dec2023 (11.49), December 20236.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMozilla Public License 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava, ScalaC++
Server operating systemsAll OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Linux
macOS
Windows
Data schemeyesyesyes infoRDF schemas
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.no
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL 2003 with some extensionsSQL-like query languageno
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
gRPC
HTTP REST
WebSocket
RESTful HTTP API
SPARQL 1.1
Supported programming languagesC++
Java
PHP
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
Scala
C
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in SQL, C, Rno
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tablesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoSource-replica replication available in experimental statusreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardRoles, resources, and access types

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HiveMonetDBNSDbRDFox
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