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DBMS > Atos Standard Common Repository vs. Prometheus vs. RDF4J vs. Sphinx vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. Prometheus vs. RDF4J vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonPrometheus  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 networksOpen-source Time Series DBMS and monitoring systemRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open 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
Time Series DBMSRDF storeSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryprometheus.iordf4j.orgsphinxsearch.comsplicemachine.com
Technical documentationprometheus.io/­docsrdf4j.org/­documentationsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sphinx Technologies Inc.Splice Machine
Initial release20162015200420012014
Current release17033.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open 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 languageJavaGoJavaC++Java
Server operating systemsLinuxLinux
Windows
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesyes infoRDF Schemasyesyes
Typing infopredefined data types such as float or dateoptionalNumeric data onlyyesnoyes
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.yesno infoImport of XML data possible
Secondary indexesyesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)yes
APIs and other access methodsLDAPRESTful HTTP/JSON APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
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 proceduresnonoyesnoyes infoJava
Triggersyesnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnoneSharding 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 nodesyesyes infoby FederationnonenoneMulti-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 configurationnoneImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID infoIsolation support depends on the API usednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes 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
User concepts infoAccess controlLDAP bind authenticationnononoAccess rights for users, groups and roles according to SQL-standard

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Atos Standard Common RepositoryPrometheusRDF4J infoformerly known as SesameSphinxSplice Machine
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