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DBMS > Netezza vs. Prometheus vs. Spark SQL vs. STSdb

System Properties Comparison Netezza vs. Prometheus vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSTime Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.ibm.com/­products/­netezzaprometheus.iospark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMApache Software FoundationSTS Soft SC
Initial release2000201520142011
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC#
Server operating systemsLinux infoincluded in applianceLinux
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes infoprimitive types and user defined types (classes)
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.no infoImport of XML data possibleno
Secondary indexesyesnonono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
OLE DB
RESTful HTTP/JSON APIJDBC
ODBC
.NET Client API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoby Federationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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 conceptnonono

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More resources
Netezza infoAlso called PureData System for Analytics by IBMPrometheusSpark SQLSTSdb
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