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DBMS > EventStoreDB vs. NSDb vs. Spark SQL vs. Valentina Server

System Properties Comparison EventStoreDB vs. NSDb vs. Spark SQL vs. Valentina Server

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Scalable, 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 processingObject-relational database and reports server
Primary database modelEvent StoreTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#173  Overall
#1  Event Stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.eventstore.comnsdb.iospark.apache.org/­sqlwww.valentina-db.net
Technical documentationdevelopers.eventstore.comnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperEvent Store LimitedApache Software FoundationParadigma Software
Initial release2012201720141999
Current release21.2, February 20213.5.0 ( 2.13), September 20235.7.5
License infoCommercial or Open SourceOpen SourceOpen 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 languageJava, ScalaScala
Server operating systemsLinux
Windows
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyes: 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.nono
Secondary indexesall fields are automatically indexednoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC
HTTP REST
WebSocket
JDBC
ODBC
ODBC
Supported programming languagesJava
Scala
Java
Python
R
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonoyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
EventStoreDBNSDbSpark SQLValentina Server
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