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DBMS > Netezza vs. Teradata vs. Vertica vs. Yaacomo

System Properties Comparison Netezza vs. Teradata vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTeradata  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA hybrid cloud data analytics software platform (Teradata Vantage)Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.teradata.comwww.vertica.comyaacomo.com
Technical documentationdocs.teradata.comvertica.com/­documentation
DeveloperIBMTeradataOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2000198420052009
Current releaseTeradata Vantage 1.0 MU2, January 201912.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinux infoincluded in appliancehosted
Linux
LinuxAndroid
Linux
Windows
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
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.yesnono
Secondary indexesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLyesyes infoSQL 2016 + extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJDBC
ODBC
OLE DB
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes infoUDFs, stored procedures, table functions in parallelyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoHashinghorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.yesnoyes
User concepts infoAccess controlUsers with fine-grained authorization conceptfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMTeradataVertica infoOpenText™ Vertica™Yaacomo
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Netezza infoAlso called PureData System for Analytics by IBMTeradataVertica infoOpenText™ Vertica™Yaacomo
DB-Engines blog posts

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

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