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DBMS > Hive vs. IRONdb vs. Microsoft Access vs. RDF4J vs. Splice Machine

System Properties Comparison Hive vs. IRONdb vs. Microsoft Access vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Access  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 HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)RDF4J 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 DBMSTime Series DBMSRelational DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/www.microsoft.com/­en-us/­microsoft-365/­accessrdf4j.orgsplicemachine.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddeveloper.microsoft.com/­en-us/­accessrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.MicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20122017199220042014
Current release3.1.3, April 2022V0.10.20, January 20181902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBundled with Microsoft OfficeOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++JavaJava
Server operating systemsAll OS with a Java VMLinuxWindows infoNot a real database server, but making use of DLLsLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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.no
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)yes infobut not compliant to any SQL standardnoyes
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIADO.NET
DAO
ODBC
OLE DB
Java 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++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luayes infosince Access 2010 using the ACE-engineyesyes infoJava
Triggersnonoyes infosince Access 2010 using the ACE-engineyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenonenoneMulti-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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infobut no files for transaction loggingACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes 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.noyes
User concepts infoAccess controlAccess rights for users, groups and rolesnono infoa simple user-level security was built in till version Access 2003noAccess rights for users, groups and roles according to SQL-standard

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More resources
HiveIRONdbMicrosoft AccessRDF4J infoformerly known as SesameSplice Machine
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