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DBMS > Faircom EDGE vs. Kinetica vs. RDF4J vs. Solr

System Properties Comparison Faircom EDGE vs. Kinetica vs. RDF4J vs. Solr

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Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value store
Relational DBMS
Relational DBMSRDF storeSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.faircom.com/­products/­faircom-edgewww.kinetica.comrdf4j.orgsolr.apache.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.kinetica.comrdf4j.org/­documentationsolr.apache.org/­resources.html
DeveloperFairCom CorporationKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release1979201220042006
Current releaseV3, October 20207.1, August 20219.6.1, May 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2
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++C, C++JavaJava
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
LinuxLinux
OS X
Unix
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infoRDF Schemasyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyesyes infosupports customizable data types and automatic typing
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.yesnoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infoANSI SQL queriesSQL-like DML and DDL statementsnoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsyesJava plugins
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoIsolation support depends on the API usedoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users and roles on table levelnoyes

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More resources
Faircom EDGE infoformerly c-treeEDGEKineticaRDF4J infoformerly known as SesameSolr
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