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DBMS > FatDB vs. NSDb vs. OrigoDB vs. Spark SQL vs. Transbase

System Properties Comparison FatDB vs. NSDb vs. OrigoDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable, 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 resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Key-value store
Time 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
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitensdb.ioorigodb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationnsdb.io/­Architectureorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperFatCloudRobert Friberg et alApache Software FoundationTransaction Software GmbH
Initial release201220172009 infounder the name LiveDB20141987
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java, ScalaC#ScalaC and C++
Server operating systemsWindowsLinux
macOS
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringUser defined using .NET types and collectionsyesyes
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 .NETnono
Secondary indexesyesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query languagenoSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#Java
Scala
.NetJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infovia applicationsnoyesnoyes
Triggersyes infovia applicationsyes infoDomain Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonodepending on modelnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsRole based authorizationnofine grained access rights according to SQL-standard

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More resources
FatDBNSDbOrigoDBSpark SQLTransbase
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