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DBMS > FatDB vs. Realm vs. Spark SQL vs. Yaacomo

System Properties Comparison FatDB vs. Realm vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiterealm.iospark.apache.org/­sqlyaacomo.com
Technical documentationrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudRealm, acquired by MongoDB in May 2019Apache Software FoundationQ2WEB GmbH
Initial release2012201420142009
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#Scala
Server operating systemsWindowsAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Android
Linux
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 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
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsno inforuns within the applications so server-side scripts are unnecessaryno
Triggersyes infovia applicationsyes infoChange Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneSource-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 datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yes infoIn-Memory realmnoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsyesnofine grained access rights according to SQL-standard

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More resources
FatDBRealmSpark SQLYaacomo
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