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DBMS > Hive vs. Spark SQL vs. Trafodion vs. Valentina Server

System Properties Comparison Hive vs. Spark SQL vs. Trafodion vs. Valentina Server

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparisonValentina Server  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMSObject-relational database and reports server
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score64.82
Rank#18  Overall
#12  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.18
Rank#331  Overall
#145  Relational DBMS
Websitehive.apache.orgspark.apache.org/­sqltrafodion.apache.orgwww.valentina-db.net
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software Foundation, originally developed by HPParadigma Software
Initial release2012201420141999
Current release3.1.3, April 20223.5.0 ( 2.13), September 20232.3.0, February 20195.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++, Java
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
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.nono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
ADO.NET
JDBC
ODBC
ODBC
Supported programming languagesC++
Java
PHP
Python
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored Proceduresyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and rolesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
HiveSpark SQLTrafodionValentina Server
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