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DBMS > FatDB vs. InterSystems Caché vs. Spark SQL

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-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
Score3.06
Rank#100  Overall
#18  Key-value stores
#1  Object oriented DBMS
#52  Relational DBMS
Score23.04
Rank#35  Overall
#21  Relational DBMS
Websitewww.intersystems.com/­products/­cachespark.apache.org/­sql
Technical documentationdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudInterSystemsApache Software Foundation
Initial release201219972014
Current release2018.1.4, May 20203.3.0, June 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
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 languageC#Scala
Server operating systemsWindowsAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freedepending 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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#C#
C++
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesno
Triggersyes infovia applicationsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesno

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More resources
FatDBInterSystems CachéSpark SQL
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