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DBMS > Atos Standard Common Repository vs. Faircom EDGE vs. Splice Machine vs. Sqrrl

System Properties Comparison Atos Standard Common Repository vs. Faircom EDGE vs. Splice Machine vs. Sqrrl

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSplice Machine  Xexclude from comparisonSqrrl  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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 environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument store
Key-value store
Key-value store
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-edgesplicemachine.comsqrrl.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsFairCom CorporationSplice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release2016197920142012
Current release1703V3, October 20203.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaJava
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesschema-free
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.yesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesyesno
APIs and other access methodsLDAPADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yes infoJavano
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionFile partitioning infoCustomizable business rules for partitioningShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)yes
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.yesyesyes
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 roles according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Atos Standard Common RepositoryFaircom EDGE infoformerly c-treeEDGESplice MachineSqrrl
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