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DBMS > FatDB vs. searchxml vs. Spark SQL vs. Transbase

System Properties Comparison FatDB vs. searchxml vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonsearchxml  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.DBMS for structured and unstructured content wrapped with an application serverSpark 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
Native XML DBMS
Search engine
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.01
Rank#386  Overall
#7  Native XML DBMS
#24  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitewww.searchxml.net/­category/­productsspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationwww.searchxml.net/­support/­handoutsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperFatCloudinformationpartners gmbhApache Software FoundationTransaction Software GmbH
Initial release2012201520141987
Current release1.03.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infofree development license
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 languageC#C++ScalaC and C++
Server operating systemsWindowsWindowsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#C++ infomost other programming languages supported via APIsJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infovia applicationsyes infoon the application servernoyes
Triggersyes infovia applicationsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infosychronisation to multiple collectionsnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writernoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsDomain, group and role-based access control at the document level and for application servicesnofine grained access rights according to SQL-standard

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More resources
FatDBsearchxmlSpark SQLTransbase
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