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DBMS > Apache Pinot vs. Teradata Aster vs. Vertica

System Properties Comparison Apache Pinot vs. Teradata Aster vs. Vertica

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Editorial information provided by DB-Engines
NameApache Pinot  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.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyPlatform 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 DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitepinot.apache.orgwww.vertica.com
Technical documentationdocs.pinot.apache.orgvertica.com/­documentation
DeveloperApache Software Foundation and contributorsTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520052005
Current release1.0.0, September 202312.0.3, 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 systemsAll OS with a Java JDK11 or higherLinuxLinux
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 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.yes infoin Aster File Storeno
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCADO.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 languagesGo
Java
Python
C
C#
C++
Java
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresR packagesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes 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 methodsyes infoSQL Map-Reduce Frameworkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes
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 persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine 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 PinotTeradata 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
Apache PinotTeradata AsterVertica infoOpenText™ Vertica™
Recent citations in the news

Real-Time Analytics for Mobile App Crashes using Apache Pinot
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Vertica by OpenText and Anritsu Sign New Deal for Next-Gen Architecture and 5G Network Capabilities
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OpenText expands enterprise portfolio with AI and Micro Focus integrations
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