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DBMS > Teradata vs. Valentina Server vs. Vertica

System Properties Comparison Teradata vs. Valentina Server vs. Vertica

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Editorial information provided by DB-Engines
NameTeradata  Xexclude from comparisonValentina Server  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA hybrid cloud data analytics software platform (Teradata Vantage)Object-relational database and reports serverCloud 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
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.teradata.comwww.valentina-db.netwww.vertica.com
Technical documentationdocs.teradata.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpvertica.com/­documentation
DeveloperTeradataParadigma SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release198419992005
Current releaseTeradata Vantage 1.0 MU2, January 20195.7.512.0.3, 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 systemshosted
Linux
Linux
OS X
Windows
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 indexesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoSQL 2016 + extensionsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ODBCADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoUDFs, stored procedures, table functions in parallelyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoHashinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
TeradataValentina ServerVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
TeradataValentina ServerVertica infoOpenText™ Vertica™
DB-Engines blog posts

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