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DBMS > Datomic vs. Kyligence Enterprise vs. Realm vs. Spark SQL

System Properties Comparison Datomic vs. Kyligence Enterprise vs. Realm vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed analytics engine for big data, built on top of Apache KylinA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comkyligence.io/­kyligence-enterpriserealm.iospark.apache.org/­sql
Technical documentationdocs.datomic.comrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectKyligence, Inc.Realm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release2012201620142014
Current release1.0.7075, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaScala
Server operating systemsAll OS with a Java VMLinuxAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)noSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsno inforuns within the applications so server-side scripts are unnecessaryno
TriggersBy using transaction functionsyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneyes, utilizing Spark Core
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 methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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 developmentnoyes infoIn-Memory realmno
User concepts infoAccess controlnoyesno

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DatomicKyligence EnterpriseRealmSpark SQL
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