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DBMS > Amazon Aurora vs. FatDB vs. InfluxDB vs. Oracle Berkeley DB vs. Spark SQL

System Properties Comparison Amazon Aurora vs. FatDB vs. InfluxDB vs. Oracle Berkeley DB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonFatDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonOracle Berkeley DB  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.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA .NET NoSQL DBMS that can integrate with and extend SQL Server.DBMS for storing time series, events and metricsWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Key-value store
Time Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.influxdata.com/­products/­influxdb-overviewwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.influxdata.com/­influxdbdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonFatCloudOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release20152012201319942014
Current release2.7.6, April 202418.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infocommercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#GoC, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemshostedWindowsLinux
OS X infothrough Homebrew
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumeric data and Stringsnoyes
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 infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServerSQL-like query languageyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
JSON over UDP
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#.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsnonono
Triggersyesyes infovia applicationsnoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoin enterprise version onlynoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorselectable replication factor infoin enterprise version onlySource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoDepending on used storage engineyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationssimple rights management via user accountsnono
More information provided by the system vendor
Amazon AuroraFatDBInfluxDBOracle Berkeley DBSpark SQL
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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