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DBMS > Hive vs. IRONdb vs. RDF4J vs. Riak KV vs. Splice Machine

System Properties Comparison Hive vs. IRONdb vs. RDF4J vs. Riak KV vs. Splice Machine

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  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 simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Distributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRDF storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orgsplicemachine.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.OpenSource, formerly Basho TechnologiesSplice Machine
Initial release20122017200420092014
Current release3.1.3, April 2022V0.10.20, January 20183.2.0, December 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL 3.0, commercial license available
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++JavaErlangJava
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoRDF Schemasschema-freeyes
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.nono
Secondary indexesyesnoyesrestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)nonoyes
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
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
Java
PHP
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in LuayesErlangyes infoJava
Triggersnonoyesyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneSharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenoneselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and rolesnonoyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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More resources
HiveIRONdbRDF4J infoformerly known as SesameRiak KVSplice Machine
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