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

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

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  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 distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument store
Relational 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
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
nsdb.iospark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationgithub.com/­apache/­doris/­wikinsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperApache Software Foundation, originally contributed from BaiduApache Software FoundationYandex
Initial release2017201720142019
Current release1.2.2, February 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0; commercial license available
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
Linux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)
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.nononono
Secondary indexesyesall fields are automatically indexednoyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsJDBC
MySQL client
gRPC
HTTP REST
WebSocket
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesJavaJava
Scala
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneActive-passive shard 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 integritynononono
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights defined for Yandex Cloud users

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More resources
Apache DorisNSDbSpark SQLYDB
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