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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. Postgres-XL vs. Prometheus vs. ReductStore

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. Postgres-XL vs. Prometheus vs. ReductStore

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPrometheus  Xexclude from comparisonReductStore  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 PlatformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-source Time Series DBMS and monitoring systemDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelDocument store
Key-value store
Document storeRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorewww.postgres-xl.orgprometheus.iogithub.com/­reductstore
www.reduct.store
Technical documentationcloud.google.com/­datastore/­docswww.postgres-xl.org/­documentationprometheus.io/­docswww.reduct.store/­docs
DeveloperAtos Convergence CreatorsGoogleReductStore LLC
Initial release201620082014 infosince 2012, originally named StormDB20152023
Current release170310 R1, October 20181.9, March 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0Open Source infoBusiness Source License 1.1
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 languageJavaCGoC++, Rust
Server operating systemsLinuxhostedLinux
macOS
Linux
Windows
Docker
Linux
macOS
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalyes, details hereyesNumeric data only
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.yesnoyes infoXML type, but no XML query functionalityno infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infodistributed, parallel query executionno
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON APIHTTP API
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsno
TriggersyesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
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.Immediate Consistencynone
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
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 TransactionsACID infoMVCCno
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 authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastorePostgres-XLPrometheusReductStore
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