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DBMS > Atos Standard Common Repository vs. Datomic vs. InterSystems Caché vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. Datomic vs. InterSystems Caché vs. Splice Machine

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatomic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA multi-model DBMS and application serverOpen-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 DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.datomic.comwww.intersystems.com/­products/­cachesplicemachine.com
Technical documentationdocs.datomic.comdocs.intersystems.comsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsCognitectInterSystemsSplice Machine
Initial release2016201219972014
Current release17031.0.6735, June 20232018.1.4, May 20203.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ClojureJava
Server operating systemsLinuxAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesdepending on used data modelyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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.yesnoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsLDAPRESTful HTTP API.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindingsClojure
Java
C#
C++
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyesyes infoJava
TriggersyesBy using transaction functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnone infoBut extensive use of caching in the application peersnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, 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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlLDAP bind authenticationnoAccess rights for users, groups and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryDatomicInterSystems CachéSplice Machine
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