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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonVitess  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 RDBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score0.11
Rank#341  Overall
#150  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.datomic.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlvitess.io
Technical documentationdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.htmlvitess.io/­docs
DeveloperCognitectApache Software FoundationTransaction Software GmbHThe Linux Foundation, PlanetScale
Initial release2012201419872013
Current release1.0.6735, June 20233.5.0 ( 2.13), September 2023Transbase 8.3, 202215.0.2, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercial infofree development licenseOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureScalaC and C++Go
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Docker
Linux
macOS
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesClojure
Java
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyesyes infoproprietary syntax
TriggersBy using transaction functionsnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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 developmentnonoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
DatomicSpark SQLTransbaseVitess
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