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DBMS > Apache Doris vs. Kinetica vs. Vertica

System Properties Comparison Apache Doris vs. Kinetica vs. Vertica

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonKinetica  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolFully vectorized database across both GPUs and CPUsCloud 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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.kinetica.comwww.vertica.com
Technical documentationgithub.com/­apache/­doris/­wikidocs.kinetica.comvertica.com/­documentation
DeveloperApache Software Foundation, originally contributed from BaiduKineticaOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201720122005
Current release1.2.2, February 20237.1, August 202112.0.3, 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, C++C++
Server operating systemsLinuxLinuxLinux
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.nonono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, 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 nodesnoneSource-replica replicationMulti-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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DorisKineticaVertica 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 DorisKineticaVertica infoOpenText™ Vertica™
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Data Analytics: Apache Doris' Impact in Reporting, Tagging, and Data Lake Operations
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