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DBMS > Datomic vs. Spark SQL vs. Tkrzw

System Properties Comparison Datomic vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.datomic.comspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectApache Software FoundationMikio Hirabayashi
Initial release201220142020
Current release1.0.7075, December 20233.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScalaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
macOS
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Supported programming languagesClojure
Java
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsnono
TriggersBy using transaction functionsnono
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 peersnonenone
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
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 developmentnoyes infousing specific database classes
User concepts infoAccess controlnonono

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DatomicSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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