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DBMS > Faircom EDGE vs. Solr vs. Spark SQL vs. STSdb vs. Trafodion

System Properties Comparison Faircom EDGE vs. Solr vs. Spark SQL vs. STSdb vs. Trafodion

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFairCom 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 LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Relational DBMS
Search engineRelational DBMSKey-value storeRelational DBMS
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
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgesolr.apache.orgspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4trafodion.apache.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperFairCom CorporationApache Software FoundationApache Software FoundationSTS Soft SCApache Software Foundation, originally developed by HP
Initial release19792006201420112014
Current releaseV3, October 20209.6.1, May 20243.5.0 ( 2.13), September 20234.0.8, September 20152.3.0, February 2019
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaScalaC#C++, Java
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
WindowsLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyesyesyes
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyes infosupports customizable data types and automatic typingyesyes infoprimitive types and user defined types (classes)yes
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.yesyesnono
Secondary indexesyesyes infoAll search fields are automatically indexednonoyes
SQL infoSupport of SQLyes infoANSI SQL queriesSolr Parallel SQL InterfaceSQL-like DML and DDL statementsnoyes
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
.NET Client APIADO.NET
JDBC
ODBC
Supported programming languagesC
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
Java
Python
R
Scala
C#
Java
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Java pluginsnonoJava Stored Procedures
Triggersyesyes infoUser configurable commands triggered on index changesnonono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyesnonenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnonoACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yesnonofine grained access rights according to SQL-standard

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More resources
Faircom EDGE infoformerly c-treeEDGESolrSpark SQLSTSdbTrafodion
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