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DBMS > 4D vs. Atos Standard Common Repository vs. BigObject vs. Sqrrl vs. Teradata Aster

System Properties Comparison 4D vs. Atos Standard Common Repository vs. BigObject vs. Sqrrl vs. Teradata Aster

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBigObject  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 networksAnalytic DBMS for real-time computations and queriesAdaptable, secure NoSQL built on Apache AccumuloPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS infoa hierachical model (tree) can be imposedDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.80
Rank#111  Overall
#55  Relational DBMS
Score0.17
Rank#333  Overall
#146  Relational DBMS
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorybigobject.iosqrrl.com
Technical documentationdeveloper.4d.comdocs.bigobject.io
Developer4D, IncAtos Convergence CreatorsBigObject, Inc.Amazon infooriginally Sqrrl Data, Inc.Teradata
Initial release19842016201520122005
Current releasev20, April 20231703
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
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
LinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux
Data schemeyesSchema and schema-less with LDAP viewsyesschema-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 dateyesoptionalyesyesyes
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 DML and DDL statementsnoyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPfluentd
ODBC
RESTful HTTP 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 bindingsActionscript
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 proceduresyesnoLuanoR packages
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionnoneSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesnoneselectable 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 methodsnonoyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate 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 infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/write lock on objects (tables, trees)yesyes
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.noyesyesno
User concepts infoAccess controlUsers and groupsLDAP bind authenticationnoCell-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 RepositoryBigObjectSqrrlTeradata Aster
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