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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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 environmentsA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsSpatial 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
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgesolr.apache.orgyaacomo.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsolr.apache.org/­resources.html
DeveloperCognitectFairCom CorporationApache Software FoundationQ2WEB GmbH
Initial release2012197920062009
Current release1.0.6735, June 2023V3, October 20209.6.0, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availableOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureANSI C, C++Java
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes infosupports customizable data types and automatic typingyes
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.noyesyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesSolr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.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 changesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningShardinghorizontal partitioning
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 logsyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.yesfine grained access rights according to SQL-standard

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGESolrYaacomo
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