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DBMS > FatDB vs. Linter vs. Spark SQL vs. STSdb

System Properties Comparison FatDB vs. Linter vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonLinter  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  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.RDBMS for high security requirementsSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitelinter.ruspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudrelex.ruApache Software FoundationSTS Soft SC
Initial release2012199020142011
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
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 and C++ScalaC#
Server operating systemsWindowsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Windows
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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 indexesyesyesnono
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like DML and DDL statementsno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
ODBC
.NET Client API
Supported programming languagesC#C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infovia applicationsyes infoproprietary syntax with the possibility to convert from PL/SQLnono
Triggersyes infovia applicationsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.no
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardnono

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More resources
FatDBLinterSpark SQLSTSdb
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