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DBMS > GeoSpock vs. InterSystems Caché vs. Spark SQL vs. Yanza

System Properties Comparison GeoSpock vs. InterSystems Caché vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded 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.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleA multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comwww.intersystems.com/­products/­cachespark.apache.org/­sqlyanza.com
Technical documentationdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockInterSystemsApache Software FoundationYanza
Initial release199720142015
Current release2.0, September 20192018.1.4, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptScala
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Windows
Data schemeyesdepending on used data modelyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesnono
Secondary indexestemporal, categoricalyesnono
SQL infoSupport of SQLANSI SQL for query only (using Presto)yesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
HTTP API
Supported programming languagesC#
C++
Java
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and rolesnono

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More resources
GeoSpockInterSystems CachéSpark SQLYanza
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