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DBMS > Atos Standard Common Repository vs. BigchainDB vs. Faircom EDGE vs. Netezza vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Faircom EDGE vs. Netezza vs. Snowflake

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBigchainDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSnowflake  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsData warehouse and analytics appliance part of IBM PureSystemsCloud-based data warehousing service for structured and semi-structured data
Primary database modelDocument store
Key-value store
Document storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.82
Rank#212  Overall
#36  Document stores
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score123.20
Rank#9  Overall
#6  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.comwww.faircom.com/­products/­faircom-edgewww.ibm.com/­products/­netezzawww.snowflake.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.snowflake.net/­manuals/­index.html
DeveloperAtos Convergence CreatorsFairCom CorporationIBMSnowflake Computing Inc.
Initial release20162016197920002014
Current release1703V3, October 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL v3commercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonANSI C, C++
Server operating systemsLinuxLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux infoincluded in appliancehosted
Data schemeSchema and schema-less with LDAP viewsschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes infosupport of semi-structured data formats (JSON, XML, Avro)
Typing infopredefined data types such as float or dateoptionalnoyes, 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.yesnoyesyes
Secondary indexesyesyesyes
SQL infoSupport of SQLnonoyes infoANSI SQL queriesyesyes
APIs and other access methodsLDAPCLI Client
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
CLI Client
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C++
Fortran
Java
Lua
Perl
Python
R
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesuser defined functions
Triggersyesyesnono infosimilar concept for controling cloud resources
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingFile partitioning infoCustomizable business rules for partitioningShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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 integritynonoyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlLDAP bind authenticationyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Users with fine-grained authorization conceptUsers with fine-grained authorization concept, user roles and pluggable authentication

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More resources
Atos Standard Common RepositoryBigchainDBFaircom EDGE infoformerly c-treeEDGENetezza infoAlso called PureData System for Analytics by IBMSnowflake
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