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DBMS > Datomic vs. RDF4J vs. Spark SQL vs. TimescaleDB vs. Transbase

System Properties Comparison Datomic vs. RDF4J vs. Spark SQL vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityRDF4J 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 processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRDF storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.datomic.comrdf4j.orgspark.apache.org/­sqlwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software FoundationTimescaleTransaction Software GmbH
Initial release20122004201420171987
Current release1.0.6735, June 20233.5.0 ( 2.13), September 20232.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaScalaCC and C++
Server operating systemsAll OS with a Java VMLinux
OS X
Unix
Windows
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyes infoRDF Schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsRESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
Java
PHP
Python
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
TriggersBy using transaction functionsyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnonenoneSource-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoIsolation support depends on the API usednoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infoin-memory storage is supported as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnonono
User concepts infoAccess controlnononofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
DatomicRDF4J infoformerly known as SesameSpark SQLTimescaleDBTransbase
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