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DBMS > Datomic vs. Splice Machine

System Properties Comparison Datomic vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.31
Rank#134  Overall
#65  Relational DBMS
Score0.75
Rank#255  Overall
#119  Relational DBMS
Websitewww.datomic.comsplicemachine.com
Technical documentationdocs.datomic.comsplicemachine.com/­how-it-works
DeveloperCognitectSplice Machine
Initial release20122014
Current release1.0.6735, June 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.no
Secondary indexesyesyes
SQL infoSupport of SQLnoyes
APIs and other access methodsRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infoJava
TriggersBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
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 developmentyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicSplice Machine
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2 November 2012, InfoQ.com

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