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DBMS > 4D vs. Atos Standard Common Repository vs. Dragonfly vs. Splice Machine vs. Teradata Aster

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Dragonfly vs. Splice Machine vs. Teradata Aster

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDragonfly  Xexclude from comparisonSplice Machine  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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Key-value store
Key-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
splicemachine.com
Technical documentationdeveloper.4d.comwww.dragonflydb.io/­docssplicemachine.com/­how-it-works
Developer4D, IncAtos Convergence CreatorsDragonflyDB team and community contributorsSplice MachineTeradata
Initial release19842016202320142005
Current releasev20, April 202317031.0, March 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSL 1.1Open Source infoAGPL 3.0, commercial license availablecommercial
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 languageJavaC++Java
Server operating systemsOS X
Windows
LinuxLinuxLinux
OS X
Solaris
Windows
Linux
Data schemeyesSchema and schema-less with LDAP viewsscheme-freeyesFlexible 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 dateyesoptionalstrings, hashes, lists, sets, sorted sets, bit arraysyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLyes infoclose to SQL 92nonoyesyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPProprietary protocol infoRESP - REdis Serialization ProtocolJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnoLuayes infoJavaR packages
Triggersyesyespublish/subscribe channels provide some trigger functionalityyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesSource-replica replicationMulti-source replication
Source-replica replication
yes 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, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsAtomic execution of command blocks and scriptsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryes, multi-version concurrency control (MVCC)yes
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.noyesyesyesno
User concepts infoAccess controlUsers and groupsLDAP bind authenticationPassword-based authenticationAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
4D infoformer name: 4th DimensionAtos Standard Common RepositoryDragonflySplice MachineTeradata Aster
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