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DBMS > HBase vs. IRONdb vs. Quasardb vs. RDF4J

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

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonQuasardb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityDistributed, high-performance timeseries databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelWide column storeTime Series 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
Score0.06
Rank#317  Overall
#28  Time Series DBMS
Score0.16
Rank#278  Overall
#22  Time Series DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Websitehbase.apache.orgwww.irondb.iowww.quasardb.netrdf4j.org
Technical documentationhbase.apache.orgwww.irondb.io/­docsdoc.quasardb.netrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.quasardbSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720092004
Current release2.2.0, June 2019V0.10.20, January 20183.1, January 2019
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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 systemsLinux
Unix
Windows infousing Cygwin
LinuxBSD
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeschema-free, schema definition possibleschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes infotext, numeric, histogramsyes infointeger and binaryyes
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 indexesnonoyes infowith tagsyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query languageno
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP APIHTTP 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++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes, in Luanoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awareSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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 dataSingle row ACID (across millions of columns)noACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes 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.yesnoyes infoTransient mode
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoCryptographically strong user authentication and audit trailno
More information provided by the system vendor
HBaseIRONdbQuasardbRDF4J infoformerly known as Sesame
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
High performance in a cost-effective small package Real-time results for even large...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Tick database Predictive maintenance Pre-deal checks Large scale monitoring
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Large EU investment banks US based hedge funds Orolia Tellmeplus
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Has been running in very demanding production environments since 2013 Rapid adoption...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more
Community edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

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More resources
HBaseIRONdbQuasardbRDF4J infoformerly known as Sesame
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