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DBMS > EXASOL vs. IRONdb vs. Microsoft Azure SQL Database vs. RDF4J vs. Splice Machine

System Properties Comparison EXASOL vs. IRONdb vs. Microsoft Azure SQL Database vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityDatabase as a Service offering with high compatibility to Microsoft SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRDF storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.exasol.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­en-us/­products/­azure-sql/­databaserdf4j.orgsplicemachine.com
Technical documentationwww.exasol.com/­resourcesdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­azure-sqlrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperExasolCirconus LLC.MicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20002017201020042014
Current releaseV0.10.20, January 2018V123.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++JavaJava
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes 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.nonoyes
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesSQL-like query language (Circonus Analytics Query Language: CAQL)yesnoyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
HTTP APIADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes, in LuaTransact SQLyesyes infoJava
Triggersyesnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareyes, with always 3 replicas availablenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
EXASOLIRONdbMicrosoft Azure SQL Database infoformerly SQL AzureRDF4J infoformerly known as SesameSplice Machine
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