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DBMS > HBase vs. IRONdb vs. MemSQL vs. RDF4J

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

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonMemSQL  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 simplicityMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storageRDF4J 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
Secondary database modelsDocument 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
Score5.50
Rank#64  Overall
#35  Relational DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Websitehbase.apache.orgwww.irondb.iowww.memsql.comrdf4j.org
Technical documentationhbase.apache.orgwww.irondb.io/­docsdocs.memsql.comrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.MemSQL Inc.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720132004
Current release2.2.0, June 2019V0.10.20, January 20187.1.4, July 2020
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercial infofree developer edition availableOpen 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
LinuxLinux info64 bit version requiredLinux
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)yes, but no triggers and foreign keysno
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP APIJDBC
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
Bash
C
C#
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes, in Luayesyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awareSource-replica replicationnone
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 only within each node
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)noACID infoOnly isolation level: READ COMMITEDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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 & ABACnofine grained access rights according to SQL-standardno
More information provided by the system vendor
HBaseIRONdbMemSQLRDF4J 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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HBaseIRONdbMemSQLRDF4J infoformerly known as Sesame
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