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DBMS > Apache Doris vs. Apache Impala vs. GeoSpock vs. Spark SQL

System Properties Comparison Apache Doris vs. Apache Impala vs. GeoSpock vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Impala  Xexclude from comparisonGeoSpock  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAnalytic DBMS for HadoopSpatial and temporal data processing engine for extreme data scaleSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
impala.apache.orggeospock.comspark.apache.org/­sql
Technical documentationgithub.com/­apache/­doris/­wikiimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation infoApache top-level project, originally developed by ClouderaGeoSpockApache Software Foundation
Initial release201720132014
Current release1.2.2, February 20234.1.0, June 20222.0, September 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java, JavascriptScala
Server operating systemsLinuxLinuxhostedLinux
OS X
Windows
Data schemeyesyesyesyes
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 indexesyesyestemporal, categoricalno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsANSI SQL for query only (using Presto)SQL-like DML and DDL statements
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
JDBCJDBC
ODBC
Supported programming languagesJavaAll languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per tableno

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More resources
Apache DorisApache ImpalaGeoSpockSpark SQL
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