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DBMS > FatDB vs. FileMaker vs. Netezza vs. Spark SQL

System Properties Comparison FatDB vs. FileMaker vs. Netezza vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonFileMaker  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Data warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.claris.com/­filemakerwww.ibm.com/­products/­netezzaspark.apache.org/­sql
Technical documentationwww.claris.com/­resources/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudClaris infoa subsidiary of AppleIBMApache Software Foundation
Initial release2012198320002014
Current release19.4.1, November 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#Scala
Server operating systemsWindowsiOS infoclient part only
Linux
OS X
Windows
Linux infoincluded in applianceLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes infoA http query request can return the data in XML formatno
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryes infovia pluginsyesSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Filemaker WebDirect
JDBC
ODBC
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesC#PHPC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesyesno
Triggersyes infovia applicationsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication, warm standby infosince Version 14Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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.no
User concepts infoAccess controlno infoCan implement custom security layer via applicationssimple rights management via user accounts and connection to external directory servicesUsers with fine-grained authorization conceptno

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FatDBFileMakerNetezza infoAlso called PureData System for Analytics by IBMSpark SQL
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