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

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

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRisingWave  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.A distributed RDBMS for stream processing, wire-compatible with PostgreSQLOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRDF storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.58
Rank#245  Overall
#112  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orgwww.risingwave.com/­databasesplicemachine.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationdocs.risingwave.com/­docs/­current/­introsplicemachine.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.RisingWave LabsSplice Machine
Initial release20122017200420222014
Current release3.1.3, April 2022V0.10.20, January 20181.2, September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2.0Open 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++JavaRustJava
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Docker
Linux
macOS
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoRDF Schemasyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesStandard SQL-types and JSONyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)noyesyes
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
JDBC
PostgreSQL wire protocol
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
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in LuayesUDFs in Python or Javayes infoJava
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable 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 consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 datayesyesyesyes, 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and rolesnonoUsers and RolesAccess rights for users, groups and roles according to SQL-standard

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More resources
HiveIRONdbRDF4J infoformerly known as SesameRisingWaveSplice Machine
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