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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTinkerGraph  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpark 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 lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APIA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSTime Series DBMSGraph 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.datomic.comspark.apache.org/­sqlwww.timescale.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectApache Software FoundationTimescaleTransaction Software GmbH
Initial release20122014201720091987
Current release1.0.7075, December 20233.5.0 ( 2.13), September 20232.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open 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, ClojureScalaCJavaC and C++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyesyes
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.nonoyesnono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
TinkerPop 3ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Groovy
Java
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellnoyes
TriggersBy using transaction functionsnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneSource-replica replication with hot standby and reads on replicas infononeSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonoyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesoptionalyes
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 developmentnonoyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
DatomicSpark SQLTimescaleDBTinkerGraphTransbase
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