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DBMS > Greenplum vs. Pinecone vs. Teradata Aster vs. Vertica

System Properties Comparison Greenplum vs. Pinecone vs. Teradata Aster vs. Vertica

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Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonPinecone  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A managed, cloud-native vector databasePlatform for big data analytics on multistructured data sources and typesCloud 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 DBMSVector DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegreenplum.orgwww.pinecone.iowww.vertica.com
Technical documentationdocs.greenplum.orgdocs.pinecone.io/­docs/­overviewvertica.com/­documentation
DeveloperPivotal Software Inc.Pinecone Systems, IncTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2005201920052005
Current release7.0.0, September 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono 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 languageC++
Server operating systemsLinuxhostedLinuxLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File StoreYes, 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 dateyesString, Number, Booleanyesyes
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.yes infosince Version 4.2noyes infoin Aster File Storeno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
Java
Perl
Python
R
PythonC
C#
C++
Java
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesR packagesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.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 methodsyesnoyes infoSQL Map-Reduce Frameworkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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.nononono
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
GreenplumPineconeTeradata AsterVertica 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
GreenplumPineconeTeradata AsterVertica infoOpenText™ Vertica™
DB-Engines blog posts

Vector databases
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