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DBMS > Datomic vs. InterSystems Caché vs. Spark SQL

System Properties Comparison Datomic vs. InterSystems Caché vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational 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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comwww.intersystems.com/­products/­cachespark.apache.org/­sql
Technical documentationdocs.datomic.comdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectInterSystemsApache Software Foundation
Initial release201219972014
Current release1.0.6735, June 20232018.1.4, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScala
Server operating systemsAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesdepending on used data modelyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
Java
C#
C++
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesno
TriggersBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes 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.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnoAccess rights for users, groups and rolesno

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DatomicInterSystems CachéSpark SQL
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