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

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

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpatiaLite  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 processingSpatial extension of SQLite
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSSpatial DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Websiteaws.amazon.com/­rds/­auroraspark.apache.org/­sqlwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperAmazonFatCloudApache Software FoundationAlessandro Furieri
Initial release2015201220142008
Current release3.5.0 ( 2.13), September 20235.0.0, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#ScalaC++
Server operating systemshostedWindowsLinux
OS X
Windows
server-less
Data schemeyesschema-freeyesyes
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.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
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
Server-side scripts infoStored proceduresyesyes infovia applicationsnono
Triggersyesyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 applicationsnono

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More resources
Amazon AuroraFatDBSpark SQLSpatiaLite
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