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DBMS > FatDB vs. Kinetica vs. Percona Server for MongoDB vs. searchxml vs. Spark SQL

System Properties Comparison FatDB vs. Kinetica vs. Percona Server for MongoDB vs. searchxml vs. Spark SQL

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonKinetica  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonsearchxml  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.Fully vectorized database across both GPUs and CPUsA drop-in replacement for MongoDB Community Edition with enterprise-grade features.DBMS for structured and unstructured content wrapped with an application serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSDocument storeNative XML DBMS
Search engine
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.52
Rank#254  Overall
#39  Document stores
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comwww.percona.com/­mongodb/­software/­percona-server-for-mongodbwww.searchxml.net/­category/­productsspark.apache.org/­sql
Technical documentationdocs.kinetica.comdocs.percona.com/­percona-distribution-for-mongodbwww.searchxml.net/­support/­handoutsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudKineticaPerconainformationpartners gmbhApache Software Foundation
Initial release20122012201520152014
Current release7.1, August 20213.4.10-2.10, November 20171.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C, C++C++C++Scala
Server operating systemsWindowsLinuxLinuxWindowsLinux
OS X
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSONRESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
ODBC
Supported programming languagesC#C++
Java
JavaScript (Node.js)
Python
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
C++ infomost other programming languages supported via APIsJava
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functionsJavaScriptyes infoon the application serverno
Triggersyes infovia applicationsyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationyes infosychronisation to multiple collectionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononomultiple readers, single writerno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes infovia In-Memory Enginenono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users and roles on table levelAccess rights for users and rolesDomain, group and role-based access control at the document level and for application servicesno

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More resources
FatDBKineticaPercona Server for MongoDBsearchxmlSpark SQL
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