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DBMS > Amazon Aurora vs. FatDB vs. Spark SQL vs. Virtuoso

System Properties Comparison Amazon Aurora vs. FatDB vs. Spark SQL vs. Virtuoso

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonVirtuoso  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processingVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.27
Rank#73  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#39  Relational DBMS
#2  RDF stores
#9  Search engines
Websiteaws.amazon.com/­rds/­auroraspark.apache.org/­sqlvirtuoso.openlinksw.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.openlinksw.com/­virtuoso
DeveloperAmazonFatCloudApache Software FoundationOpenLink Software
Initial release2015201220141998
Current release3.5.0 ( 2.13), September 20237.2.11, September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaC
Server operating systemshostedWindowsLinux
OS X
Windows
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes infoSQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type
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.yesnoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#Java
Python
R
Scala
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresyesyes infovia applicationsnoyes infoVirtuoso PL
Triggersyesyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Coreyes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factornoneChain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationsnoFine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Amazon AuroraFatDBSpark SQLVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale โ€” as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for โ€” Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including โ€” European Union (EU) US Government...
» more
Market metricsLargest installed-base โ€‹of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsAvailable in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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More resources
Amazon AuroraFatDBSpark SQLVirtuoso
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