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DBMS > Hive vs. IRONdb vs. MarkLogic vs. RDF4J

System Properties Comparison Hive vs. IRONdb vs. MarkLogic vs. RDF4J

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonMarkLogic  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOperational and transactional Enterprise NoSQL databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.50
Rank#14  Overall
#9  Relational DBMS
Score0.00
Rank#347  Overall
#31  Time Series DBMS
Score9.92
Rank#44  Overall
#7  Document stores
#1  Native XML DBMS
#1  RDF stores
#4  Search engines
Score0.54
Rank#225  Overall
#9  RDF stores
Websitehive.apache.orgwww.circonus.com/­solutions/­time-series-databasewww.marklogic.comrdf4j.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/­irondbdocs.marklogic.comrdf4j.org/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.MarkLogic Corp.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2012201720012004
Current release3.1.2, August 2019V0.10.20, January 20189.0, 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial inforestricted free version is availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++Java
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes
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.noyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)yes infoSQL92no
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luayes infovia XQuery or JavaScriptyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infocan act as a resource manager in an XA/JTA transactionACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexes
User concepts infoAccess controlAccess rights for users, groups and rolesnoRole-based access control at the document and subdocument levelsno
More information provided by the system vendor
HiveIRONdbMarkLogicRDF4J infoformerly known as Sesame
Specific characteristicsThe MarkLogic Multi-Model Database provides the simplest way to integrate data from...
» more
Competitive advantagesThe main benefit of MarkLogic is simplicity. By making things simpler, MarkLogic...
» more
Typical application scenariosMarkLogic’s main use case is the Operational Data Hub . A Data Hub is useful for...
» more
Key customersMarkLogic has proven results managing mission-critical data with over 1,000 global...
» more
Market metricsMarkLogic is well known within the Fortune 1000, with a strong presence in financial...
» more
Licensing and pricing modelsMarkLogic provides a variety of licenses and cloud services: MarkLogic Data Hub Service...
» more

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HiveIRONdbMarkLogicRDF4J infoformerly known as Sesame
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