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DBMS > Netezza vs. Newts vs. Quasardb vs. Spark SQL

System Properties Comparison Netezza vs. Newts vs. Quasardb vs. Spark SQL

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonNewts  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsTime Series DBMS based on CassandraDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score0.19
Rank#327  Overall
#30  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­netezzaopennms.github.io/­newtsquasar.aispark.apache.org/­sql
Technical documentationgithub.com/­OpenNMS/­newts/­wikidoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMOpenNMS GroupquasardbApache Software Foundation
Initial release2000201420092014
Current release3.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Scala
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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 indexesyesnoyes infowith tagsno
SQL infoSupport of SQLyesnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP REST
Java API
HTTP APIJDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandraSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlUsers with fine-grained authorization conceptnoCryptographically strong user authentication and audit trailno

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More resources
Netezza infoAlso called PureData System for Analytics by IBMNewtsQuasardbSpark SQL
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