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

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

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonPostGIS  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 capabilitiesSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Relational DBMS
Spatial DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.leanxcale.compostgis.netspark.apache.org/­sqltrafodion.apache.org
Technical documentationpostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperLeanXcaleApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2015200520142014
Current release3.4.2, February 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCScalaC++, Java
Server operating systemsLinux
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLyes infothrough Apache DerbyyesSQL-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
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Procedures
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesyes infobased on PostgreSQLyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infobased on PostgreSQLnoneyes, 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 integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnonono
User concepts infoAccess controlyes infobased on PostgreSQLnofine grained access rights according to SQL-standard

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More resources
LeanXcalePostGISSpark SQLTrafodion
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