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DBMS > HBase vs. Infobright vs. IRONdb vs. RDF4J

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

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonInfobright  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendA 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 modelWide column storeRelational DBMSTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score49.11
Rank#22  Overall
#2  Wide column stores
Score1.12
Rank#155  Overall
#76  Relational DBMS
Score0.06
Rank#317  Overall
#28  Time Series DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Websitehbase.apache.orgwww.ignitetech.com/­solutions/­information-technology/­infobrightdbwww.irondb.iordf4j.org
Technical documentationhbase.apache.orgwww.irondb.io/­docsrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetIgnite Technologies Inc.; formerly InfoBright Inc.Circonus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008200520172004
Current release2.2.0, June 2019V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache version 2commercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC and C++Java
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
Windows
LinuxLinux
OS X
Unix
Windows
Data schemeschema-free, schema definition possibleyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateoptions 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 indexesnono infoKnowledge Grid Technology used insteadnoyes
SQL infoSupport of SQLnoyesSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsJava API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
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
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.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 proceduresyes infoCoprocessors in Javanoyes, in Luayes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACIDnoACID 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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesnono
More information provided by the system vendor
HBaseInfobrightIRONdbRDF4J infoformerly known as Sesame
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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HBaseInfobrightIRONdbRDF4J infoformerly known as Sesame
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