DBMS > 4D vs. Atos Standard Common Repository vs. DataFS vs. Google Cloud Datastore

System Properties Comparison 4D vs. Atos Standard Common Repository vs. DataFS vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
Name	4D former name: 4th Dimension  Xexclude from comparison	Atos Standard Common Repository  Xexclude from comparison	DataFS  Xexclude from comparison	Google Cloud Datastore  Xexclude from comparison
		This system has been discontinued and will be removed from the DB-Engines ranking.
Description	Application development environment with integrated database management system	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.	Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database model	Relational DBMS	Document store Key-value store	Object oriented DBMS	Document store
Secondary database models			Graph DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 2.47 Rank #110   Overall #54   Relational DBMS		Score 0.09 Rank #360   Overall #18   Object oriented DBMS	Score 4.36 Rank #72   Overall #12   Document stores
Website	www.4d.com	atos.net/en/convergence-creators/portfolio/standard-common-repository	newdatabase.com	cloud.google.com/­datastore
Technical documentation	developer.4d.com		dev.mobiland.com/­Overview.xsp	cloud.google.com/­datastore/­docs
Developer	4D, Inc	Atos Convergence Creators	Mobiland AG	Google
Initial release	1984	2016	2018	2008
Current release	v20, April 2023	1703	1.1.263, October 2022
License Commercial or Open Source	commercial	commercial	commercial	commercial
Cloud-based only Only available as a cloud service	no	no	no	yes
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language		Java
Server operating systems	OS X Windows	Linux	Windows	hosted
Data scheme	yes	Schema and schema-less with LDAP views	Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)	schema-free
Typing predefined data types such as float or date	yes	optional	yes	yes, details here
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	yes	yes	no	no
Secondary indexes	yes	yes	no	yes
SQL Support of SQL	yes close to SQL 92	no	no	SQL-like query language (GQL)
APIs and other access methods	ODBC RESTful HTTP API by using 4D Mobile SOAP webservices	LDAP	.NET Client API Proprietary client DLL WinRT client	gRPC (using protocol buffers) API RESTful HTTP/JSON API
Supported programming languages	4D proprietary IDE PHP	All languages with LDAP bindings	.Net C C# C++ VB.Net	.Net Go Java JavaScript (Node.js) PHP Python Ruby
Server-side scripts Stored procedures	yes	no		using Google App Engine
Triggers	yes	yes	no, except callback-events from server when changes happened	Callbacks using the Google Apps Engine
Partitioning methods Methods for storing different data on different nodes	none	Sharding cell division	Proprietary Sharding system	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	Multi-source replication	yes		Multi-source replication using Paxos
MapReduce Offers an API for user-defined Map/Reduce methods	no		no	yes using Google Cloud Dataflow
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong 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 Referential integrity	yes	no	yes	yes via ReferenceProperties or Ancestor paths
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	Atomic execution of specific operations	ACID	ACID Serializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	no	yes	no	no
User concepts Access control	Users and groups	LDAP bind authentication	Windows-Profile	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
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More resources
	4D former name: 4th Dimension	Atos Standard Common Repository	DataFS	Google Cloud Datastore
DB-Engines blog posts	MySQL, PostgreSQL and Redis are the winners of the March ranking 2 March 2016, Paul Andlinger show all
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