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DBMS > FatDB vs. Memcached vs. OushuDB vs. Spark SQL

System Properties Comparison FatDB vs. Memcached vs. OushuDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonMemcached  Xexclude from comparisonOushuDB  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.In-memory key-value store, originally intended for cachingA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.08
Rank#32  Overall
#4  Key-value stores
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.memcached.orgwww.oushu.com/­product/­oushuDBspark.apache.org/­sql
Technical documentationgithub.com/­memcached/­memcached/­wikiwww.oushu.com/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalOushuApache Software Foundation
Initial release201220032014
Current release1.6.27, May 20244.0.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialOpen 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#CScala
Server operating systemsWindowsFreeBSD
Linux
OS X
Unix
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.no
Secondary indexesyesnoyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoFull-featured ANSI SQL supportSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Proprietary protocolJDBC
ODBC
JDBC
ODBC
Supported programming languagesC#.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C
C++
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsnoyesno
Triggersyes infovia applicationsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
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 persistentyesnoyesyes
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 applicationsyes infousing SASL (Simple Authentication and Security Layer) protocolKerberos, SSL and role based accessno

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More resources
FatDBMemcachedOushuDBSpark SQL
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