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DBMS > atoti vs. InterSystems Caché vs. Prometheus vs. Splice Machine

System Properties Comparison atoti vs. InterSystems Caché vs. Prometheus vs. Splice Machine

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonPrometheus  Xexclude from comparisonSplice Machine  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A multi-model DBMS and application serverOpen-source Time Series DBMS and monitoring systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelObject oriented DBMSKey-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatoti.iowww.intersystems.com/­products/­cacheprometheus.iosplicemachine.com
Technical documentationdocs.atoti.iodocs.intersystems.comprometheus.io/­docssplicemachine.com/­how-it-works
DeveloperActiveViamInterSystemsSplice Machine
Initial release199720152014
Current release2018.1.4, May 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache 2.0Open 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 languageJavaGoJava
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Windows
Linux
OS X
Solaris
Windows
Data schemedepending on used data modelyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyes
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 indexesyesnoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesnoyes
APIs and other access methods.NET Client API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresPythonyesnoyes infoJava
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoby FederationMulti-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 ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users, groups and rolesnoAccess rights for users, groups and roles according to SQL-standard

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atotiInterSystems CachéPrometheusSplice Machine
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