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DBMS > atoti vs. RDF4J vs. Splice Machine

System Properties Comparison atoti vs. RDF4J vs. Splice Machine

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.RDF4J 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 modelObject oriented DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatoti.iordf4j.orgsplicemachine.com
Technical documentationdocs.atoti.iordf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperActiveViamSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20042014
Current release3.1, March 2021
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes
Secondary indexesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noyes
APIs and other access methodsJava 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
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresPythonyesyes infoJava
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes 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.yesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standard

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More resources
atotiRDF4J infoformerly known as SesameSplice Machine
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