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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBrytlyt  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  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 GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLGeode 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 Platform
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorybrytlyt.iogeode.apache.orgcloud.google.com/­datastore
Technical documentationdocs.brytlyt.iogeode.apache.org/­docscloud.google.com/­datastore/­docs
DeveloperAtos Convergence CreatorsBrytlytOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Google
Initial release2016201620022008
Current release17035.0, August 20231.1, February 2017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial
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 languageJavaC, C++ and CUDAJava
Server operating systemsLinuxLinux
OS X
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredhosted
Data schemeSchema and schema-less with LDAP viewsyesschema-freeschema-free
Typing infopredefined data types such as float or dateoptionalyesyesyes, details here
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 functionality.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like query language (OQL)SQL-like query language (GQL)
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLuser defined functionsusing Google App Engine
Triggersyesyesyes infoCache Event ListenersCallbacks using the Google Apps Engine
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 replicationMulti-source replication using Paxos
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 ConsistencyEventual 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 integritynoyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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 authenticationfine grained access rights according to SQL-standardAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Atos Standard Common RepositoryBrytlytGeodeGoogle Cloud Datastore
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