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

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonsearchxml  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  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 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 processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Key-value store
Document storeNative XML DBMS
Search engine
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.percona.com/­mongodb/­software/­percona-server-for-mongodbwww.searchxml.net/­category/­productsspark.apache.org/­sqlwww.tigergraph.com
Technical documentationdocs.percona.com/­percona-distribution-for-mongodbwww.searchxml.net/­support/­handoutsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperFatCloudPerconainformationpartners gmbhApache Software Foundation
Initial release20122015201520142017
Current release3.4.10-2.10, November 20171.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL Version 2commercialOpen Source infoApache 2.0commercial
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++ScalaC++
Server operating systemsWindowsLinuxWindowsLinux
OS X
Windows
Linux
Data schemeschema-freeschema-freeschema-freeyesyes
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
proprietary protocol using JSONRESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#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
C++
Java
Server-side scripts infoStored proceduresyes infovia applicationsJavaScriptyes infoon the application servernoyes
Triggersyes infovia applicationsnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infosychronisation to multiple collectionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonomultiple readers, single writernoACID
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 infovia In-Memory Enginenonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users and rolesDomain, group and role-based access control at the document level and for application servicesnoRole-based access control

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More resources
FatDBPercona Server for MongoDBsearchxmlSpark SQLTigerGraph
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