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DBMS > Hive vs. IRONdb vs. RDF4J vs. XAP

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

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonXAP  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 simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.High performant in-memory data grid for mission critical applications. Insight Edge from the same company extends XAP for AI/ML support, BI and other interfaces
Primary database modelRelational DBMSTime Series DBMSRDF storeDocument store
Key-value store infoValues are user defined objects
Secondary database modelsObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.65
Rank#14  Overall
#9  Relational DBMS
Score0.06
Rank#312  Overall
#27  Time Series DBMS
Score0.48
Rank#215  Overall
#9  RDF stores
Score0.84
Rank#169  Overall
#27  Document stores
#31  Key-value stores
Websitehive.apache.orgwww.irondb.iordf4j.orgwww.gigaspaces.com/­products/­xap
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docsrdf4j.org/­documentationdocs.gigaspaces.com/­latest/­landing.html
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Gigaspaces Technologies
Initial release2012201720042000
Current release3.1.2, August 2019V0.10.20, January 201814.5.0, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2; Commercial licenses available
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++JavaJava, C++, .Net
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyes infoRDF Schemasschema-free
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.nono infoXML can be used for describing objects metadata
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like query language and DML statements
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
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
Java
PHP
Python
.Net
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luayesyes
Triggersnonoyesyes infoEvent Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneSharding infoHash based
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenoneMaster-master replication infosynchronous or asynchronous
Master-slave replication infosynchronous or asynchronous
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and rolesnonoRole-based access control
More information provided by the system vendor
HiveIRONdbRDF4J infoformerly known as SesameXAP
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more

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HiveIRONdbRDF4J infoformerly known as SesameXAP
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