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DBMS > GridDB vs. HBase vs. IRONdb vs. RDF4J

System Properties Comparison GridDB vs. HBase vs. IRONdb vs. RDF4J

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableA 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 modelTime Series DBMSWide column storeTime Series DBMSRDF store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score0.71
Rank#231  Overall
#9  RDF stores
Websitegriddb.nethbase.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmldocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013200820172004
Current release5.1, August 20222.3.4, January 2021V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2commercialOpen 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 languageC++JavaC and C++Java
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Unix
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyes 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 indexesyesnonoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.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, in Luayes
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelSingle row ACID (across millions of columns)noACID 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.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
GridDBHBaseIRONdbRDF4J infoformerly known as Sesame
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
GridDBHBaseIRONdbRDF4J infoformerly known as Sesame
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