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DBMS > Oracle NoSQL vs. Spark SQL vs. YTsaurus

System Properties Comparison Oracle NoSQL vs. Spark SQL vs. YTsaurus

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Editorial information provided by DB-Engines
NameOracle NoSQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonYTsaurus  Xexclude from comparison
DescriptionA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesSpark SQL is a component on top of 'Spark Core' for structured data processingYTsaurus is an open source platform for distributed storage and processing.
Primary database modelDocument store
Key-value store
Relational DBMS
Relational DBMSDocument store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#340  Overall
#45  Document stores
#50  Key-value stores
Websitewww.oracle.com/­database/­nosql/­technologies/­nosqlspark.apache.org/­sqlytsaurus.tech
Technical documentationdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlytsaurus.tech/­docs/­en
DeveloperOracleApache Software FoundationYandex
Initial release201120142023
Current release23.3, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoApache 2.0Open Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemsLinux
Solaris SPARC/x86
Linux
OS X
Windows
Ubuntu
Data schemeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
Typing infopredefined data types such as float or dateoptionalyesyes
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.nonono
Secondary indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsYQL, an SQL-based language, is supported
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesElectable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodswith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataconfigurable infoACID within a storage node (=shard)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infooff heap cacheno
User concepts infoAccess controlAccess rights for users and rolesnoAccess Control Lists

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More resources
Oracle NoSQLSpark SQLYTsaurus
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