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DBMS > Datomic vs. Faircom EDGE vs. RDFox vs. Solr

System Properties Comparison Datomic vs. Faircom EDGE vs. RDFox vs. Solr

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonRDFox  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsHigh performance knowledge graph and semantic reasoning engineA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Relational DBMS
Graph DBMS
RDF store
Search engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgewww.oxfordsemantic.techsolr.apache.org
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.oxfordsemantic.techsolr.apache.org/­resources.html
DeveloperCognitectFairCom CorporationOxford Semantic TechnologiesApache Software Foundation
Initial release2012197920172006
Current release1.0.6735, June 2023V3, October 20206.0, Septermber 20229.6.0, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availablecommercialOpen 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 languageJava, ClojureANSI C, C++C++Java
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes infoRDF schemasyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes 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.noyesyes
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyes infoANSI SQL queriesnoSolr Parallel SQL Interface
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
Java
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++Java plugins
TriggersBy using transaction functionsyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsreplication via a shared file systemyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsEventual Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyesyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Roles, resources, and access typesyes

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGERDFoxSolr
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