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DBMS > Fauna vs. IRONdb vs. MonetDB vs. RDF4J vs. Spark SQL

System Properties Comparison Fauna vs. IRONdb vs. MonetDB vs. RDF4J vs. Spark SQL

Editorial information provided by DB-Engines
NameFauna infopreviously named FaunaDB  Xexclude from comparisonIRONdb  Xexclude from comparisonMonetDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA relational database management system that stores data in columnsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSRDF storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefauna.comwww.circonus.com/solutions/time-series-database/www.monetdb.orgrdf4j.orgspark.apache.org/­sql
Technical documentationdocs.fauna.comdocs.circonus.com/irondb/category/getting-startedwww.monetdb.org/­Documentationrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFauna, Inc.Circonus LLC.MonetDB BVSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release20142017200420042014
Current releaseV0.10.20, January 2018Dec2023 (11.49), December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC and C++CJavaScala
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or datenoyes infotext, numeric, histogramsyesyesyes
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 indexesyesnoyesyesno
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)yes infoSQL 2003 with some extensionsnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIHTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes, in Luayes, in SQL, C, Ryesno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingAutomatic, metric affinity per nodeSharding via remote tablesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationconfigurable replication factor, datacenter awarenone infoSource-replica replication available in experimental statusnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlIdentity management, authentication, and access controlnofine grained access rights according to SQL-standardnono

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Fauna infopreviously named FaunaDBIRONdbMonetDBRDF4J infoformerly known as SesameSpark SQL
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