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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. JanusGraph vs. Linter vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. JanusGraph vs. Linter vs. SWC-DB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonLinter  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 networksAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017RDBMS for high security requirementsA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Key-value store
Document storeGraph DBMSRelational DBMSWide column store
Secondary database modelsSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorejanusgraph.orglinter.rugithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationcloud.google.com/­datastore/­docsdocs.janusgraph.org
DeveloperAtos Convergence CreatorsGoogleLinux Foundation; originally developed as Titan by Aureliusrelex.ruAlex Kashirin
Initial release20162008201719902020
Current release17030.6.3, February 20230.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++C++
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateoptionalyes, details hereyesyes
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.yesnononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyesSQL-like query language
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Proprietary protocol
Thrift
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C++
Server-side scripts infoStored proceduresnousing Google App Engineyesyes infoproprietary syntax with the possibility to convert from PL/SQLno
TriggersyesCallbacks using the Google Apps Engineyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)noneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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.Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastoreJanusGraph infosuccessor of TitanLinterSWC-DB infoSuper Wide Column Database
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