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DBMS > Apache Doris vs. Apache Impala vs. Realm vs. Vertica

System Properties Comparison Apache Doris vs. Apache Impala vs. Realm vs. Vertica

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Impala  Xexclude from comparisonRealm  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAnalytic DBMS for HadoopA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataCloud 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 DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#235  Overall
#110  Relational DBMS
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score7.18
Rank#52  Overall
#8  Document stores
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
impala.apache.orgrealm.iowww.vertica.com
Technical documentationgithub.com/­apache/­doris/­wikiimpala.apache.org/­impala-docs.htmlrealm.io/­docsvertica.com/­documentation
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation infoApache top-level project, originally developed by ClouderaRealm, acquired by MongoDB in May 2019OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201320142005
Current release1.2.2, February 20234.1.0, June 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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++
Server operating systemsLinuxLinuxAndroid
Backend: server-less
iOS
Windows
Linux
Data schemeyesyesyesYes, 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 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.nononono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaAll languages supporting JDBC/ODBC.Net
Java infowith Android only
Objective-C
React Native
Swift
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-reduceno inforuns within the applications so server-side scripts are unnecessaryyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infoChange Listenersyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factornoneMulti-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 methodsnoyes infoquery execution via MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 infoIn-Memory realmno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache DorisApache ImpalaRealmVertica infoOpenText™ Vertica™
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