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DBMS > FatDB vs. Oracle Rdb vs. Quasardb vs. Spark SQL

System Properties Comparison FatDB vs. Oracle Rdb vs. Quasardb vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonOracle Rdb  Xexclude from comparisonQuasardb  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.Distributed, high-performance timeseries databaseSpark 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.oracle.com/­database/­technologies/­related/­rdb.htmlquasar.aispark.apache.org/­sql
Technical documentationwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmldoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudOracle, originally developed by Digital Equipment Corporation (DEC)quasardbApache Software Foundation
Initial release2012198420092014
Current release7.4.1.1, 20213.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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++Scala
Server operating systemsWindowsHP Open VMSBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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 indexesyesyesyes infowith tagsno
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
HTTP APIJDBC
ODBC
Supported programming languagesC#.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsnono
Triggersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsCryptographically strong user authentication and audit trailno

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FatDBOracle RdbQuasardbSpark SQL
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