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DBMS > Apache Phoenix vs. Teradata vs. Vertica

System Properties Comparison Apache Phoenix vs. Teradata vs. Vertica

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonTeradata  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitephoenix.apache.orgwww.teradata.comwww.vertica.com
Technical documentationphoenix.apache.orgdocs.teradata.comvertica.com/­documentation
DeveloperApache Software FoundationTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201419842005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019Teradata Vantage 1.0 MU2, January 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial 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

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Implementation languageJavaC++
Server operating systemsLinux
Unix
Windows
hosted
Linux
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesYes, 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.noyesno
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.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#
C++
Go
Groovy
Java
PHP
Python
Scala
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 proceduresuser defined functionsyes 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 nodesMulti-source replication
Source-replica replication
Multi-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 methodsHadoop integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate 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.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine 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
Apache PhoenixTeradataVertica infoOpenText™ Vertica™
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
Apache PhoenixTeradataVertica infoOpenText™ Vertica™
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

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1 May 2024, The Register

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30 April 2024, InfoWorld

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OCI Object Storage Completes Technical Validation of Vertica in Eon Mode
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