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DBMS > GeoSpock vs. HBase vs. Hive vs. IRONdb vs. RDF4J

System Properties Comparison GeoSpock vs. HBase vs. Hive vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleWide-column store based on Apache Hadoop and on concepts of BigTabledata 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.
Primary database modelRelational DBMSWide column storeRelational DBMSTime Series DBMSRDF store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score31.25
Rank#26  Overall
#2  Wide column stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websitegeospock.comhbase.apache.orghive.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationhbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperGeoSpockApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201220172004
Current release2.0, September 20192.3.4, January 20213.1.3, April 2022V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaJavaC and C++Java
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VMLinuxLinux
OS X
Unix
Windows
Data schemeyesschema-free, schema definition possibleyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infotext, numeric, histogramsyes
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.nonono
Secondary indexestemporal, categoricalnoyesnoyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)noSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsJDBCJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
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
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceyes, in Luayes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)nonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesnono

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GeoSpockHBaseHiveIRONdbRDF4J infoformerly known as Sesame
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