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DBMS > Faircom EDGE vs. Microsoft Azure Table Storage vs. Oracle Coherence vs. Solr

System Properties Comparison Faircom EDGE vs. Microsoft Azure Table Storage vs. Oracle Coherence vs. Solr

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Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOracle Coherence  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 environmentsA Wide Column Store for rapid development using massive semi-structured datasetsOracles in-memory data grid solutionA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value store
Relational DBMS
Wide column storeKey-value storeSearch engine
Secondary database modelsSpatial 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
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.97
Rank#129  Overall
#22  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­java/­coherencesolr.apache.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.oracle.com/­en/­middleware/­standalone/­coherencesolr.apache.org/­resources.html
DeveloperFairCom CorporationMicrosoftOracleApache Software Foundation
Initial release1979201220072006
Current releaseV3, October 202014.1, August 20239.6.1, May 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaJava
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
hostedAll OS with a Java VMAll 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)schema-freeschema-freeyes 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.yesnonoyes
Secondary indexesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infoANSI SQL queriesnonoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIJCache
JPA
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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 info.Net, JavaScript, C/C++nonoJava plugins
Triggersyesnoyes infoLive Eventsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency levelyes
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 ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingconfigurableoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptionallyyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights based on private key authentication or shared access signaturesauthentification to access the cache via certificates or http basic authenticationyes

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More resources
Faircom EDGE infoformerly c-treeEDGEMicrosoft Azure Table StorageOracle CoherenceSolr
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