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DBMS > FatDB vs. Spark SQL vs. SQream DB vs. STSdb

System Properties Comparison FatDB vs. Spark SQL vs. SQream DB vs. STSdb

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  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.Spark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsKey-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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitespark.apache.org/­sqlsqream.comgithub.com/­STSSoft/­STSdb4
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperFatCloudApache Software FoundationSQream TechnologiesSTS Soft SC
Initial release2012201420172011
Current release3.5.0 ( 2.13), September 20232022.1.6, December 20224.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaC++, CUDA, Haskell, Java, ScalaC#
Server operating systemsWindowsLinux
OS X
Windows
LinuxWindows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes 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.no
Secondary indexesyesnonono
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyesno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
.Net
JDBC
ODBC
.NET Client API
Supported programming languagesC#Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C#
Java
Server-side scripts infoStored proceduresyes infovia applicationsnouser defined functions in Pythonno
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal and vertical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenonenone
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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 applicationsnono

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More resources
FatDBSpark SQLSQream DBSTSdb
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