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DBMS > EXASOL vs. Hazelcast vs. IRONdb vs. RDF4J vs. Splice Machine

System Properties Comparison EXASOL vs. Hazelcast vs. IRONdb vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparisonIRONdb  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 widely adopted in-memory data gridA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J 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 DBMSKey-value storeTime Series DBMSRDF storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.exasol.comhazelcast.comwww.circonus.com/solutions/time-series-database/rdf4j.orgsplicemachine.com
Technical documentationwww.exasol.com/­resourceshazelcast.org/­imdg/­docsdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperExasolHazelcastCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20002008201720042014
Current release5.3.6, November 2023V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaJava
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesyes
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP APIJava 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
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor Servicesyes, in Luayesyes infoJava
Triggersyesyes infoEventsnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapconfigurable replication factor, datacenter awarenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoACID 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.yesyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardRole-based access controlnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
EXASOLHazelcastIRONdbRDF4J infoformerly known as SesameSplice Machine
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