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DBMS > Apache Doris vs. Netezza vs. Spark SQL vs. SurrealDB

System Properties Comparison Apache Doris vs. Netezza vs. Spark SQL vs. SurrealDB

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.ibm.com/­products/­netezzaspark.apache.org/­sqlsurrealdb.com
Technical documentationgithub.com/­apache/­doris/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.htmlsurrealdb.com/­docs
DeveloperApache Software Foundation, originally contributed from BaiduIBMApache Software FoundationSurrealDB Ltd
Initial release2017200020142022
Current release1.2.2, February 20233.5.0 ( 2.13), September 2023v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaRust
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesyesschema-free
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.nono
Secondary indexesyesyesno
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
OLE DB
JDBC
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesJavaC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresuser defined functionsyesno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, 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 Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptnoyes, based on authentication and database rules

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More resources
Apache DorisNetezza infoAlso called PureData System for Analytics by IBMSpark SQLSurrealDB
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