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DBMS > 4D vs. Atos Standard Common Repository vs. Google Cloud Datastore vs. Sqrrl vs. Teradata Aster

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

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSqrrl  Xexclude from comparisonTeradata Aster  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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 networksAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAdaptable, secure NoSQL built on Apache AccumuloPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Key-value store
Document storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastoresqrrl.com
Technical documentationdeveloper.4d.comcloud.google.com/­datastore/­docs
Developer4D, IncAtos Convergence CreatorsGoogleAmazon infooriginally Sqrrl Data, Inc.Teradata
Initial release19842016200820122005
Current releasev20, April 20231703
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsOS X
Windows
LinuxhostedLinuxLinux
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 dateyesoptionalyes, 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.yesyesnoyes infoin Aster File Store
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyes infoclose to SQL 92noSQL-like query language (GQL)noyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnousing Google App EnginenoR packages
TriggersyesyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShardingSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesMulti-source replication using Paxosselectable replication factor infomaking use of Hadoopyes 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 methodsnoyes infousing Google Cloud Dataflowyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic updates per row, document, or graph entityACID
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.noyesnono
User concepts infoAccess controlUsers and groupsLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard

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More resources
4D infoformer name: 4th DimensionAtos Standard Common RepositoryGoogle Cloud DatastoreSqrrlTeradata Aster
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