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DBMS > 4D vs. Atos Standard Common Repository vs. Cloudflare Workers KV vs. Google Cloud Datastore vs. Teradata Aster

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Cloudflare Workers KV vs. Google Cloud Datastore vs. Teradata Aster

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTeradata Aster  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionApplication development environment with integrated database management systemHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Key-value store
Key-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#110  Overall
#54  Relational DBMS
Score0.39
Rank#278  Overall
#39  Key-value stores
Score4.49
Rank#79  Overall
#12  Document stores
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.cloudflare.com/­developer-platform/­workers-kvcloud.google.com/­datastore
Technical documentationdeveloper.4d.comdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docs
Developer4D, IncAtos Convergence CreatorsCloudflareGoogleTeradata
Initial release19842016201820082005
Current releasev20, April 20231703
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsOS X
Windows
LinuxhostedhostedLinux
Data schemeyesSchema and schema-less with LDAP viewsschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesoptionalnoyes, 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.yesyesnonoyes infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyes infoclose to SQL 92nonoSQL-like query language (GQL)yes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPHTTP REST
Proprietary protocol
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnonousing Google App EngineR packages
TriggersyesyesnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesyesMulti-source replication using Paxosyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonono
User concepts infoAccess controlUsers and groupsLDAP bind authenticationAccess 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
4D infoformer name: 4th DimensionAtos Standard Common RepositoryCloudflare Workers KVGoogle Cloud DatastoreTeradata Aster
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