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DBMS > Atos Standard Common Repository vs. Citus vs. etcd vs. Google Cloud Spanner

System Properties Comparison Atos Standard Common Repository vs. Citus vs. etcd vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCitus  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Spanner  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 PostgreSQLA distributed reliable key-value storeA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score7.64
Rank#54  Overall
#5  Key-value stores
Score2.89
Rank#105  Overall
#53  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.citusdata.cometcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­spanner
Technical documentationdocs.citusdata.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­spanner/­docs
DeveloperAtos Convergence CreatorsGoogle
Initial release201620102017
Current release17038.1, December 20183.4, August 2019
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCGo
Server operating systemsLinuxLinuxFreeBSD
Linux
Windows infoexperimental
hosted
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesnoyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsnoyes infoQuery statements complying to ANSI 2011
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyesyesyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Atos Standard Common RepositoryCitusetcdGoogle Cloud Spanner
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