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

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

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata 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 simplicityFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSKey-value storeRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/www.kinetica.comgithub.com/­google/­leveldbrdf4j.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdrdf4j.org/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.KineticaGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20122017201220112004
Current release3.1.3, April 2022V0.10.20, January 20187.1, August 20211.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoBSDOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C, C++C++Java
Server operating systemsAll OS with a Java VMLinuxLinuxIllumos
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesnoyes
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 indexesyesnoyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
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++
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
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luauser defined functionsnoyes
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesno
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 persistentyesyesyesyes infowith automatic compression on writesyes 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 controlAccess rights for users, groups and rolesnoAccess rights for users and roles on table levelnono

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More resources
HiveIRONdbKineticaLevelDBRDF4J infoformerly known as Sesame
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