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DBMS > Datomic vs. Spark SQL vs. Transbase

System Properties Comparison Datomic vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameDatomic  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 durabilitySpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.93
Rank#120  Overall
#59  Relational DBMS
Score21.39
Rank#34  Overall
#20  Relational DBMS
Score0.26
Rank#279  Overall
#129  Relational DBMS
Websitewww.datomic.comspark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperCognitectApache Software FoundationTransaction Software GmbH
Initial release201220141987
Current release0.9.5951, July 20193.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScalaC and C++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes
TriggersBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
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)yesyes
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 developmentnono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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DatomicSpark SQLTransbase
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