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

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

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.24
Rank#36  Overall
#22  Relational DBMS
Score3.50
Rank#90  Overall
#16  Document stores
Score20.84
Rank#34  Overall
#20  Relational DBMS
Score0.25
Rank#276  Overall
#128  Relational DBMS
Websitewww.ibm.com/­products/­netezzaravendb.netspark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperIBMHibernating RhinosApache Software FoundationTransaction Software GmbH
Initial release2000201020141987
Current release5.1, November 20203.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial infofree development license
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.
RavenDB Cloud: Deploy a fully managed RavenDB Cloud Database in minutes on AWS, Azure, and GCP. HIPPA compliant. Enjoy a globally distributed cluster with enterprise-grade security and reduce cloud storage costs by 50% with Native data compression.
Implementation languageC#ScalaC and C++
Server operating systemsLinux infoincluded in applianceLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (RQL)SQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
OLE DB
.NET Client API
Java Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C#
Go
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesyesnoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoMapReduce functions can be defined in Linqno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID, Cluster-wide transaction availablenoyes
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess control on document level using the Authorization Bundlenofine grained access rights according to SQL-standard
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMRavenDBSpark SQLTransbase
Specific characteristicsRavenDB is the pioneer NoSQL Document Database that is fully transactional (ACID)...
» more
Competitive advantagesRavenDB is easy to setup and secure. You can do it in a matter of minutes . Easy...
» more
Typical application scenariosIoT for Edge Deployments Fraud Detection Recommendation Engines Product Catalogs...
» more
Key customersToyota, Capgemini, Vodafone, Medicaid, Asos, Nomura, RMS Automotive, MSNBC, Pluralsight,...
» more
Market metrics2 million+ downloads 1000+ customers including Fortune 500 large enterprises
» more
Licensing and pricing modelsRavenDB is available on-premise and in the cloud. RavenDB Cloud is available on AWS...
» more

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More resources
Netezza infoAlso called PureData System for Analytics by IBMRavenDBSpark SQLTransbase
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