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DBMS > FatDB vs. Hive vs. Percona Server for MySQL vs. Spark SQL

System Properties Comparison FatDB vs. Hive vs. Percona Server for MySQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHive  Xexclude from comparisonPercona Server for MySQL  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.data warehouse software for querying and managing large distributed datasets, built on HadoopEnhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.Spark 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
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.10
Rank#119  Overall
#57  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitehive.apache.orgwww.percona.com/­software/­mysql-database/­percona-serverspark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.percona.com/­downloads/­Percona-Server-LATESTspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudApache Software Foundation infoinitially developed by FacebookPerconaApache Software Foundation
Initial release2012201220082014
Current release3.1.3, April 20228.0.36-28, 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGPL version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaC and C++Scala
Server operating systemsWindowsAll OS with a Java VMLinuxLinux
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.yesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#C++
Java
PHP
Python
Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes infouser defined functions and integration of map-reduceyesno
Triggersyes infovia applicationsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replication
Source-replica replication
XtraDB Cluster
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
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.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesUsers with fine-grained authorization concept infono user groups or rolesno

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More resources
FatDBHivePercona Server for MySQLSpark SQL
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