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DBMS > Atos Standard Common Repository vs. Faircom EDGE vs. InterSystems Caché vs. ReductStore vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Faircom EDGE vs. InterSystems Caché vs. ReductStore vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonReductStore  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA multi-model DBMS and application serverDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value store
Relational DBMS
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
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
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-edgewww.intersystems.com/­products/­cachegithub.com/­reductstore
www.reduct.store
spark.apache.org/­sql
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.intersystems.comwww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsFairCom CorporationInterSystemsReductStore LLCApache Software Foundation
Initial release20161979199720232014
Current release1703V3, October 20202018.1.4, May 20201.9, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialOpen Source infoBusiness Source License 1.1Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++C++, RustScala
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Docker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)depending on used data modelyes
Typing infopredefined data types such as float or dateoptionalyes, ANSI Standard SQL Typesyesyes
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.yesyesyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyes infoANSI SQL queriesyesSQL-like DML and DDL statements
APIs and other access methodsLDAPADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
C++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionFile partitioning infoCustomizable business rules for partitioningnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlLDAP bind authenticationFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and rolesno

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More resources
Atos Standard Common RepositoryFaircom EDGE infoformerly c-treeEDGEInterSystems CachéReductStoreSpark SQL
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