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DBMS > Atos Standard Common Repository vs. Citus vs. Sadas Engine vs. Sphinx vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. Citus vs. Sadas Engine vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCitus  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.citusdata.comwww.sadasengine.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.citusdata.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsSADAS s.r.l.Sphinx Technologies Inc.Splice Machine
Initial release20162010200620012014
Current release17038.1, December 20188.03.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availablecommercial infofree trial version availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
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 languageJavaCC++C++Java
Server operating systemsLinuxLinuxAIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesyesyesyes
Typing infopredefined data types such as float or dateoptionalyesyesnoyes
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.yesyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsyesSQL-like query language (SphinxQL)yes
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonoyes infoJava
Triggersyesyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryCitusSadas EngineSphinxSplice Machine
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