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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonRisingWave  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 distributed RDBMS for stream processing, wire-compatible with PostgreSQLSpark 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 DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.58
Rank#242  Overall
#111  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.datomic.comwww.risingwave.com/­databasespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comdocs.risingwave.com/­docs/­current/­introspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectRisingWave LabsApache Software FoundationTransaction Software GmbH
Initial release2012202220141987
Current release1.0.6735, June 20231.2, September 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0Open 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, ClojureRustScalaC and C++
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesStandard SQL-types and JSONyesyes
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 SQLnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJDBC
PostgreSQL wire protocol
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsUDFs in Python or Javanoyes
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 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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyes
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 developmentyesnono
User concepts infoAccess controlnoUsers and Rolesnofine grained access rights according to SQL-standard

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More resources
DatomicRisingWaveSpark SQLTransbase
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