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DBMS > Atos Standard Common Repository vs. Microsoft Access vs. Solr vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. Microsoft Access vs. Solr vs. Splice Machine

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  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 networksMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A widely used distributed, scalable search engine based on Apache LuceneOpen-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 DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.orgsplicemachine.com
Technical documentationdeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.htmlsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsMicrosoftApache Software FoundationSplice Machine
Initial release2016199220062014
Current release17031902 (16.0.11328.20222), March 20199.6.0, April 20243.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaJava
Server operating systemsLinuxWindows infoNot a real database server, but making use of DLLsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateoptionalyesyes infosupports customizable data types and automatic typingyes
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
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardSolr Parallel SQL Interfaceyes
APIs and other access methodsLDAPADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infosince Access 2010 using the ACE-engineJava pluginsyes infoJava
Triggersyesyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infobut no files for transaction loggingoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlLDAP bind authenticationno infoa simple user-level security was built in till version Access 2003yesAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryMicrosoft AccessSolrSplice Machine
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