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DBMS > Atos Standard Common Repository vs. Geode vs. Google Cloud Datastore vs. MonetDB

System Properties Comparison Atos Standard Common Repository vs. Geode vs. Google Cloud Datastore vs. MonetDB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMonetDB  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 networksGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA relational database management system that stores data in columns
Primary database modelDocument store
Key-value store
Key-value storeDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygeode.apache.orgcloud.google.com/­datastorewww.monetdb.org
Technical documentationgeode.apache.org/­docscloud.google.com/­datastore/­docswww.monetdb.org/­Documentation
DeveloperAtos Convergence CreatorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleMonetDB BV
Initial release2016200220082004
Current release17031.1, February 2017Dec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC
Server operating systemsLinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedFreeBSD
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyes, details hereyes
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.yesnono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnoSQL-like query language (OQL)SQL-like query language (GQL)yes infoSQL 2003 with some extensions
APIs and other access methodsLDAPJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineyes, in SQL, C, R
Triggersyesyes infoCache Event ListenersCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replication using Paxosnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesyesno
User concepts infoAccess controlLDAP bind authenticationAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGeodeGoogle Cloud DatastoreMonetDB
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