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DBMS > Apache Doris vs. Hive vs. Vertica vs. Yaacomo

System Properties Comparison Apache Doris vs. Hive vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonHive  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocoldata warehouse software for querying and managing large distributed datasets, built on HadoopCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
hive.apache.orgwww.vertica.comyaacomo.com
Technical documentationgithub.com/­apache/­doris/­wikicwiki.apache.org/­confluence/­display/­Hive/­Homevertica.com/­documentation
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation infoinitially developed by FacebookOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2017201220052009
Current release1.2.2, February 20233.1.3, April 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinuxAll OS with a Java VMLinuxAndroid
Linux
Windows
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
Thrift
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesJavaC++
Java
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DorisHiveVertica infoOpenText™ Vertica™Yaacomo
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...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
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 DorisHiveVertica infoOpenText™ Vertica™Yaacomo
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