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DBMS > EsgynDB vs. SAP HANA vs. Spark SQL vs. Trafodion

System Properties Comparison EsgynDB vs. SAP HANA vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonSAP HANA  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.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionIn-memory, column based data store. Available as appliance or cloud serviceSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score45.49
Rank#22  Overall
#16  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitewww.esgyn.cnwww.sap.com/­products/­hana.htmlspark.apache.org/­sqltrafodion.apache.org
Technical documentationhelp.sap.com/­hanaspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperEsgynSAPApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2015201020142014
Current release2.0 SPS07 (AprilĀ 4, 2023), April 20233.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono infoalso available as a cloud based servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaScalaC++, Java
Server operating systemsLinuxAppliance or cloud-serviceLinux
OS X
Windows
Linux
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 indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresJava Stored ProceduresSQLScript, RnoJava Stored Procedures
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingyesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes 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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnofine grained access rights according to SQL-standard

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More resources
EsgynDBSAP HANASpark SQLTrafodion
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