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DBMS > Apache Doris vs. Greenplum vs. NSDb vs. Spark SQL

System Properties Comparison Apache Doris vs. Greenplum vs. NSDb vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonGreenplum  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
greenplum.orgnsdb.iospark.apache.org/­sql
Technical documentationgithub.com/­apache/­doris/­wikidocs.greenplum.orgnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from BaiduPivotal Software Inc.Apache Software Foundation
Initial release2017200520172014
Current release1.2.2, February 20237.0.0, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ScalaScala
Server operating systemsLinuxLinuxLinux
macOS
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.noyes infosince Version 4.2nono
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLyesyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
gRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesJavaC
Java
Perl
Python
R
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesnono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Apache DorisGreenplumNSDbSpark SQL
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