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DBMS > Netezza vs. Prometheus vs. Teradata vs. Warp 10

System Properties Comparison Netezza vs. Prometheus vs. Teradata vs. Warp 10

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPrometheus  Xexclude from comparisonTeradata  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsOpen-source Time Series DBMS and monitoring systemA hybrid cloud data analytics software platform (Teradata Vantage)TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
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
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.ibm.com/­products/­netezzaprometheus.iowww.teradata.comwww.warp10.io
Technical documentationprometheus.io/­docsdocs.teradata.comwww.warp10.io/­content/­02_Getting_started
DeveloperIBMTeradataSenX
Initial release2000201519842015
Current releaseTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache License 2.0
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.
Implementation languageGoJava
Server operating systemsLinux infoincluded in applianceLinux
Windows
hosted
Linux
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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 possibleyesno
Secondary indexesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexno
SQL infoSupport of SQLyesnoyes infoSQL 2016 + extensionsno
APIs and other access methodsJDBC
ODBC
OLE DB
RESTful HTTP/JSON API.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesnoyes infoUDFs, stored procedures, table functions in parallelyes infoWarpScript
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoHashingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoby FederationMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyesno
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 persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Netezza infoAlso called PureData System for Analytics by IBMPrometheusTeradataWarp 10
DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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