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DBMS > HBase vs. IRONdb vs. LeanXcale vs. RDF4J

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

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonLeanXcale  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 simplicityA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelWide column storeTime Series DBMSKey-value store
Relational DBMS
RDF 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
Score0.25
Rank#264  Overall
#46  Key-value stores
#121  Relational DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Websitehbase.apache.orgwww.irondb.iowww.leanxcale.comrdf4j.org
Technical documentationhbase.apache.orgwww.irondb.io/­docsrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.LeanXcaleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720152004
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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsLinux
Unix
Windows infousing Cygwin
LinuxLinux
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, 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.nono
Secondary indexesnonoyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)yes infothrough Apache Derbyno
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP APIJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
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
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes, in Luayes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
configurable 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 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.yesnoyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
HBaseIRONdbLeanXcaleRDF4J infoformerly known as Sesame
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Full ACID and full SQL operational database with analytical queries over operational...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
15 beta testers
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more
annual fee covering license and support based on number of physical cores
» more

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More resources
HBaseIRONdbLeanXcaleRDF4J infoformerly known as Sesame
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