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DBMS > InterSystems Caché vs. Spark SQL vs. Transbase

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

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Editorial information provided by DB-Engines
NameInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.86
Rank#100  Overall
#18  Key-value stores
#1  Object oriented DBMS
#51  Relational DBMS
Score21.39
Rank#34  Overall
#20  Relational DBMS
Score0.26
Rank#279  Overall
#129  Relational DBMS
Websitewww.intersystems.com/­products/­cachespark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperInterSystemsApache Software FoundationTransaction Software GmbH
Initial release199720141987
Current release2018.1.4, May 20203.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemedepending on used data modelyesyes
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
C++
Java
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnoyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication
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 integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnono
User concepts infoAccess controlAccess rights for users, groups and rolesnofine grained access rights according to SQL-standard

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More resources
InterSystems CachéSpark SQLTransbase
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