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

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

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolScalable, 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 processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
nsdb.iospark.apache.org/­sqlwww.teradata.com
Technical documentationgithub.com/­apache/­doris/­wikinsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperApache Software Foundation, originally contributed from BaiduApache Software FoundationTeradata
Initial release2017201720141984
Current release1.2.2, February 20233.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
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 systemsLinuxLinux
macOS
Linux
OS X
Windows
hosted
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyesyes
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.nononoyes
Secondary indexesyesall fields are automatically indexednoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
MySQL client
gRPC
HTTP REST
WebSocket
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesJavaJava
Scala
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes
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-standardnofine grained access rights according to SQL-standard

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More resources
Apache DorisNSDbSpark SQLTeradata
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