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DBMS > Faircom DB vs. RDF4J vs. Splice Machine vs. UniData,UniVerse

System Properties Comparison Faircom DB vs. RDF4J vs. Splice Machine vs. UniData,UniVerse

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.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 SparkMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelKey-value store
Relational DBMS
RDF storeRelational DBMSMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitewww.faircom.com/­products/­faircom-dbrdf4j.orgsplicemachine.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlrdf4j.org/­documentationsplicemachine.com/­how-it-worksdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperFairCom CorporationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice MachineRocket Software
Initial release1979200420141985
Current releaseV12, November 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaJavaC
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,yes infoRDF Schemasyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesoptional
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 indexesyesyesyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoyesyes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yesyes infoJavayes
Triggersyesyesyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).noneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACID infoIsolation support depends on the API usedACIDACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyes 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.yesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesnoAccess rights for users, groups and roles according to SQL-standardAccess rights according to SQL-standard and operating system based

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More resources
Faircom DB infoformerly c-treeACERDF4J infoformerly known as SesameSplice MachineUniData,UniVerse
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