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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. GridGain vs. IBM Db2 Event Store

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. GridGain vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonIBM Db2 Event Store  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 PlatformGridGain is an in-memory computing platform, built on Apache IgniteDistributed Event Store optimized for Internet of Things use cases
Primary database modelDocument store
Key-value store
Document storeColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Event Store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorewww.gridgain.comwww.ibm.com/­products/­db2-event-store
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlwww.ibm.com/­docs/­en/­db2-event-store
DeveloperAtos Convergence CreatorsGoogleGridGain Systems, Inc.IBM
Initial release2016200820072017
Current release1703GridGain 8.5.12.0
License infoCommercial or Open Sourcecommercialcommercialcommercial, open sourcecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .Net, Python, REST, SQLC and C++
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
z/OS
Linux infoLinux, macOS, Windows for the developer addition
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalyes, details hereyesyes
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.yesnoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infothrough the embedded Spark runtime
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)yes
TriggersyesCallbacks using the Google Apps Engineyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes (replicated cache)Active-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
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 TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
Security Hooks for custom implementations
fine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastoreGridGainIBM Db2 Event Store
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