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DBMS > Hive vs. Netezza vs. NuoDB vs. Spark SQL vs. WakandaDB

System Properties Comparison Hive vs. Netezza vs. NuoDB vs. Spark SQL vs. WakandaDB

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonNuoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopData warehouse and analytics appliance part of IBM PureSystemsNuoDB is a webscale distributed database that supports SQL and ACID transactionsSpark SQL is a component on top of 'Spark Core' for structured data processingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.94
Rank#197  Overall
#92  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Websitehive.apache.orgwww.ibm.com/­products/­netezzawww.3ds.com/­nuodb-distributed-sql-databasespark.apache.org/­sqlwakanda.github.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedoc.nuodb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperApache Software Foundation infoinitially developed by FacebookIBMDassault Systèmes infooriginally NuoDB, Inc.Apache Software FoundationWakanda SAS
Initial release20122000201320142012
Current release3.1.3, April 20223.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ScalaC++, JavaScript
Server operating systemsAll OS with a Java VMLinux infoincluded in appliancehosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesJava, SQLnoyes
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingdata is dynamically stored/cached on the nodes where it is read/writtenyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infoManaged transparently by NuoDBnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infotunable commit protocolnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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 infoTemporary tablenono
User concepts infoAccess controlAccess rights for users, groups and rolesUsers with fine-grained authorization conceptStandard SQL roles/ privileges, Administrative Usersnoyes

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More resources
HiveNetezza infoAlso called PureData System for Analytics by IBMNuoDBSpark SQLWakandaDB
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