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DBMS > Atos Standard Common Repository vs. Citus vs. Google Cloud Datastore vs. STSdb vs. TinkerGraph

System Properties Comparison Atos Standard Common Repository vs. Citus vs. Google Cloud Datastore vs. STSdb vs. TinkerGraph

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSTSdb  Xexclude from comparisonTinkerGraph  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 networksScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Key-value store
Relational DBMSDocument storeKey-value storeGraph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.citusdata.comcloud.google.com/­datastoregithub.com/­STSSoft/­STSdb4tinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.citusdata.comcloud.google.com/­datastore/­docs
DeveloperAtos Convergence CreatorsGoogleSTS Soft SC
Initial release20162010200820112009
Current release17038.1, December 20184.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoGPLv2, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC#Java
Server operating systemsLinuxLinuxhostedWindows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateoptionalyesyes, details hereyes 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.yesyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsSQL-like query language (GQL)nono
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client APITinkerPop 3
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
Groovy
Java
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Enginenono
TriggersyesyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.none
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Atos Standard Common RepositoryCitusGoogle Cloud DatastoreSTSdbTinkerGraph
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