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DBMS > Netezza vs. Spark SQL vs. TinkerGraph vs. Transbase

System Properties Comparison Netezza vs. Spark SQL vs. TinkerGraph vs. Transbase

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonTinkerGraph  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APIA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.ibm.com/­products/­netezzaspark.apache.org/­sqltinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.transaction.de/­en/­products/­transbase.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperIBMApache Software FoundationTransaction Software GmbH
Initial release2000201420091987
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC and C++
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesschema-freeyes
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.nonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
TinkerPop 3ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Groovy
Java
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnonoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
Durability infoSupport for making data persistentyesyesoptionalyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlUsers with fine-grained authorization conceptnonofine grained access rights according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSpark SQLTinkerGraphTransbase
Recent citations in the news

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

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Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
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