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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Cloudant  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 networksA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering based on Apache CouchDB
Primary database modelDocument store
Key-value store
Key-value storeDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score2.68
Rank#106  Overall
#20  Document stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorewww.ibm.com/­products/­cloudant
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docscloud.ibm.com/­docs/­Cloudant
DeveloperAtos Convergence CreatorsDragonflyDB team and community contributorsGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release2016202320082010
Current release17031.0, March 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Erlang
Server operating systemsLinuxLinuxhostedhosted
Data schemeSchema and schema-less with LDAP viewsscheme-freeschema-freeschema-free
Typing infopredefined data types such as float or dateoptionalstrings, hashes, lists, sets, sorted sets, bit arraysyes, details hereno
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.yesnonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)no
APIs and other access methodsLDAPProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
Server-side scripts infoStored proceduresnoLuausing Google App EngineView functions (Map-Reduce) in JavaScript
Triggersyespublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual 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.Eventual Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic execution of command blocks and scriptsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a document possible
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes infoOptimistic locking
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.yesyesnono
User concepts infoAccess controlLDAP bind authenticationPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per database

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More resources
Atos Standard Common RepositoryDragonflyGoogle Cloud DatastoreIBM Cloudant
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