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DBMS > HBase vs. IRONdb vs. Microsoft Azure SQL Data Warehouse vs. RDF4J

System Properties Comparison HBase vs. IRONdb vs. Microsoft Azure SQL Data Warehouse vs. RDF4J

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure SQL Data Warehouse  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 simplicityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelWide column storeTime Series DBMSRelational 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
Score8.86
Rank#44  Overall
#27  Relational DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Websitehbase.apache.orgwww.irondb.ioazure.microsoft.com/­services/­sql-data-warehouserdf4j.org
Technical documentationhbase.apache.orgwww.irondb.io/­docsdocs.microsoft.com/­azure/­sql-data-warehouserdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.MicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720162004
Current release2.2.0, June 2019V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++Java
Server operating systemsLinux
Unix
Windows infousing Cygwin
LinuxhostedLinux
OS X
Unix
Windows
Data schemeschema-free, schema definition possibleschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes infotext, numeric, histogramsyesyes
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 indexesnonoyesyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)yesno
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP APIADO.NET
JDBC
ODBC
Java 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
C#
Java
PHP
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes, in LuaTransact SQLyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awareyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
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 integritynonoyes
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 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.yesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoyesno
More information provided by the system vendor
HBaseIRONdbMicrosoft Azure SQL Data WarehouseRDF4J 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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HBaseIRONdbMicrosoft Azure SQL Data WarehouseRDF4J infoformerly known as Sesame
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