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DBMS > FatDB vs. Linter vs. Machbase Neo vs. Spark SQL

System Properties Comparison FatDB vs. Linter vs. Machbase Neo vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonLinter  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSpark SQL  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 requirementsTimeSeries DBMS for AIoT and BigDataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMS
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
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitelinter.rumachbase.comspark.apache.org/­sql
Technical documentationmachbase.com/­dbmsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudrelex.ruMachbaseApache Software Foundation
Initial release2012199020132014
Current releaseV8.0, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree test version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C and C++CScala
Server operating systemsWindowsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query languageSQL-like DML and DDL statements
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)
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
JDBC
ODBC
Supported programming languagesC#C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
Java
Python
R
Scala
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 nodesShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationselectable replication factornone
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 persistentyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infovolatile and lookup tableno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardsimple password-based access controlno

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More resources
FatDBLinterMachbase Neo infoFormer name was InfinifluxSpark SQL
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