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DBMS > Druid vs. HBase vs. IRONdb vs. RDF4J

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

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Editorial information provided by DB-Engines
NameDruid  Xexclude from comparisonHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionOpen-source analytics data store designed for OLAP queries on timeseries 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 modelRelational DBMS
Time Series DBMS
Wide column storeTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.17
Rank#118  Overall
#59  Relational DBMS
#7  Time Series DBMS
Score49.11
Rank#22  Overall
#2  Wide column stores
Score0.06
Rank#317  Overall
#28  Time Series DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Websitedruid.apache.orghbase.apache.orgwww.irondb.iordf4j.org
Technical documentationdruid.apache.org/­docs/­latest/­designhbase.apache.orgwww.irondb.io/­docsrdf4j.org/­documentation
DeveloperMetamarkets Group and contributorsApache 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 release2012200820172004
Current release2.2.0, June 2019V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache license v2Open 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 languageJavaJavaC and C++Java
Server operating systemsLinux
OS X
Unix
Linux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Unix
Windows
Data schemeyes infoschema-less columns are supportedschema-free, schema definition possibleschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesoptions 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 SQLSQL support via Apache Calcite adapternoSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsJSON over HTTPJava 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 languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
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
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 datanoSingle 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.noyesno
User concepts infoAccess controlno infoavailable via extensionsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
DruidHBaseIRONdbRDF4J 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DruidHBaseIRONdbRDF4J infoformerly known as Sesame
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