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DBMS > Datomic vs. Realm vs. Spark SQL vs. Transbase

System Properties Comparison Datomic vs. Realm vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.datomic.comrealm.iospark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectRealm, acquired by MongoDB in May 2019Apache Software FoundationTransaction Software GmbH
Initial release2012201420141987
Current release1.0.6735, June 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen SourceOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScalaC and C++
Server operating systemsAll OS with a Java VMAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsno inforuns within the applications so server-side scripts are unnecessarynoyes
TriggersBy using transaction functionsyes infoChange Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
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 developmentyes infoIn-Memory realmnono
User concepts infoAccess controlnoyesnofine grained access rights according to SQL-standard

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DatomicRealmSpark SQLTransbase
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