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DBMS > NSDb vs. OrigoDB vs. Spark SQL vs. SQream DB

System Properties Comparison NSDb vs. OrigoDB vs. Spark SQL vs. SQream DB

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Editorial information provided by DB-Engines
NameNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelTime Series DBMSDocument store
Object oriented DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.73
Rank#228  Overall
#105  Relational DBMS
Websitensdb.ioorigodb.comspark.apache.org/­sqlsqream.com
Technical documentationnsdb.io/­Architectureorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperRobert Friberg et alApache Software FoundationSQream Technologies
Initial release20172009 infounder the name LiveDB20142017
Current release3.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ScalaC#ScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinux
macOS
Linux
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyes: int, bigint, decimal, stringUser defined using .NET types and collectionsyesyes, ANSI Standard SQL Types
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 infocan be achieved using .NETno
Secondary indexesall fields are automatically indexedyesnono
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
JDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesJava
Scala
.NetJava
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesnouser defined functions in Python
Triggersyes infoDomain Eventsnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentUsing Apache Luceneyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlRole based authorizationno

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More resources
NSDbOrigoDBSpark SQLSQream DB
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