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DBMS > ArcadeDB vs. Atos Standard Common Repository vs. Google Cloud Datastore vs. IBM Cloudant vs. TigerGraph

System Properties Comparison ArcadeDB vs. Atos Standard Common Repository vs. Google Cloud Datastore vs. IBM Cloudant vs. TigerGraph

Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonTigerGraph  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenHighly 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 PlatformDatabase as a Service offering based on Apache CouchDBA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Key-value store
Document storeDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#366  Overall
#50  Document stores
#38  Graph DBMS
#53  Key-value stores
#36  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score2.68
Rank#106  Overall
#20  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitearcadedb.comatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorewww.ibm.com/­products/­cloudantwww.tigergraph.com
Technical documentationdocs.arcadedb.comcloud.google.com/­datastore/­docscloud.ibm.com/­docs/­Cloudantdocs.tigergraph.com
DeveloperArcade DataAtos Convergence CreatorsGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release20212016200820102017
Current releaseSeptember 20211703
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaErlangC++
Server operating systemsAll OS with a Java VMLinuxhostedhostedLinux
Data schemeschema-freeSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalyes, details herenoyes
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.noyesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language, no joinsnoSQL-like query language (GQL)noSQL-like query language (GSQL)
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
LDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesJavaAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Java
Server-side scripts infoStored proceduresnousing Google App EngineView functions (Map-Reduce) in JavaScriptyes
TriggersyesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integrityyes inforelationship in graphsnoyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a document possibleACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoOptimistic lockingyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseRole-based access control

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More resources
ArcadeDBAtos Standard Common RepositoryGoogle Cloud DatastoreIBM CloudantTigerGraph
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