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DBMS > EXASOL vs. RDF4J vs. Spark SQL vs. SwayDB

System Properties Comparison EXASOL vs. RDF4J vs. Spark SQL vs. SwayDB

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.RDF4J 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 processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSRDF storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.20
Rank#80  Overall
#44  Relational DBMS
Score0.64
Rank#218  Overall
#9  RDF stores
Score21.39
Rank#34  Overall
#20  Relational DBMS
Score0.12
Rank#313  Overall
#46  Key-value stores
Websitewww.exasol.comrdf4j.orgspark.apache.org/­sqlswaydb.io
Technical documentationwww.exasol.com/­resourcesrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software FoundationSimer Plaha
Initial release2000200420142018
Current release3.1.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaScala
Server operating systemsLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesyes infoRDF Schemasyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
Java
PHP
Python
Java
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresuser defined functionsyesnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoIsolation support depends on the API usednoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnonono

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More resources
EXASOLRDF4J infoformerly known as SesameSpark SQLSwayDB
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