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DBMS > FatDB vs. Hive vs. IRONdb vs. Kinetica vs. RDF4J

System Properties Comparison FatDB vs. Hive vs. IRONdb vs. Kinetica vs. RDF4J

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.data warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityGPU-accelerated database for real-time analysis of large and streaming datasetsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#9  Relational DBMS
Score0.06
Rank#305  Overall
#26  Time Series DBMS
Score0.57
Rank#198  Overall
#96  Relational DBMS
Score0.39
Rank#220  Overall
#10  RDF stores
Websitehive.apache.orgwww.irondb.iowww.kinetica.comrdf4j.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docswww.kinetica.com/­docsdocs.rdf4j.org
DeveloperFatCloudApache Software Foundation infoinitially developed by FacebookCirconus LLC.KineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20122012201720122004
Current release3.1.2, August 2019V0.10.20, January 20186.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaC and C++C, C++Java
Server operating systemsWindowsAll OS with a Java VMLinuxLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes 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.nono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
HTTP APIJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#C++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresyes infovia applicationsyes infouser defined functions and integration of map-reduceyes, in Luauser defined functionsyes
Triggersyes infovia applicationsnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorconfigurable replication factor, datacenter awareMaster-slave replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesnoAccess rights for users and roles on table levelno
More information provided by the system vendor
FatDBHiveIRONdbKineticaRDF4J 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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More resources
FatDBHiveIRONdbKineticaRDF4J infoformerly known as Sesame
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