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DBMS > LeanXcale vs. Realm vs. Spark SQL vs. Trafodion

System Properties Comparison LeanXcale vs. Realm vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA 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 processingTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Relational DBMS
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.leanxcale.comrealm.iospark.apache.org/­sqltrafodion.apache.org
Technical documentationrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperLeanXcaleRealm, acquired by MongoDB in May 2019Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release2015201420142014
Current release3.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0Open 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 languageScalaC++, Java
Server operating systemsAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnoyes
SQL infoSupport of SQLyes infothrough Apache DerbynoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC
Java
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresno inforuns within the applications so server-side scripts are unnecessarynoJava Stored Procedures
Triggersyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoIn-Memory realmnono
User concepts infoAccess controlyesnofine grained access rights according to SQL-standard

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LeanXcaleRealmSpark SQLTrafodion
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