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DBMS > Netezza vs. Teradata vs. Vertica

System Properties Comparison Netezza vs. Teradata vs. Vertica

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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 comparison
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.
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoColumn oriented
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
Score7.34
Rank#48  Overall
#30  Relational DBMS
Score40.69
Rank#23  Overall
#16  Relational DBMS
Score10.02
Rank#42  Overall
#26  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.teradata.comwww.vertica.com
Technical documentationdocs.teradata.comvertica.com/­documentation
DeveloperIBMTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release200019842005
Current releaseTeradata Vantage 1.0 MU2, January 201912.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
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
Linux
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes
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.yesno
Secondary indexesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyes infoSQL 2016 + extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
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
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 Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoHashinghorizontal partitioning, hierarchical 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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
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 hash

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

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

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Recent citations in the news

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

RIP Netezza, IBM’s FPGA-powered data warehousing dream
3 July 2019, The Register

IBM Completes Acquisition of Netezza
26 October 2017, PR Newswire

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22 March 2023, businesswire.com

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23 October 2024, CDOTrends

TDC Stock Earnings: Teradata Beats EPS, Misses Revenue for Q1 2024
24 October 2024, MSN

Investigation Alert: MacroGenics, Apellis Pharmaceuticals,
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Teradata's SWOT analysis: cloud strength amid growth challenges By Investing.com
24 October 2024, Investing.com UK

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Vertica on Kubernetes
20 June 2024, OpenText

Vertica by OpenText and Anritsu Sign New Deal for Next-Gen Architecture and 5G Network Capabilities
17 May 2023, PR Newswire

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

Solving Big Data Challenges with Data Science at Uber
20 March 2019, Uber

VAST links arms with Vertica for fast analytics
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