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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  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 processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.datomic.comspark.apache.org/­sqlswaydb.simer.auwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectApache Software FoundationSimer PlahaTransaction Software GmbH
Initial release2012201420181987
Current release1.0.6735, June 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoGNU Affero GPL V3.0commercial 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, ClojureScalaScalaC and C++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesnonoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
Java
Python
R
Scala
Java
Kotlin
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonoyes
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes, utilizing Spark Corenone
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 dataACIDnoAtomic execution of operationsyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 developmentnoyesno
User concepts infoAccess controlnononofine grained access rights according to SQL-standard

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DatomicSpark SQLSwayDBTransbase
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