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DBMS > Hive vs. Infobright vs. IRONdb vs. RDF4J vs. Splice Machine

System Properties Comparison Hive vs. Infobright vs. IRONdb vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonInfobright  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 HadoopHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendA 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.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score1.00
Rank#193  Overall
#90  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitehive.apache.orgignitetech.com/­softwarelibrary/­infobrightdbwww.circonus.com/solutions/time-series-database/rdf4j.orgsplicemachine.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoinitially developed by FacebookIgnite Technologies Inc.; formerly InfoBright Inc.Circonus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20122005201720042014
Current release3.1.3, April 2022V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open 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 languageJavaCC and C++JavaJava
Server operating systemsAll OS with a Java VMLinux
Windows
LinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes infoRDF Schemasyes
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 indexesyesno infoKnowledge Grid Technology used insteadnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methodsJDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.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#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, in Luayesyes infoJava
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationconfigurable replication factor, datacenter awarenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
HiveInfobrightIRONdbRDF4J infoformerly known as SesameSplice Machine
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