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DBMS > Badger vs. EsgynDB vs. Spark SQL vs. Trafodion

System Properties Comparison Badger vs. EsgynDB vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonEsgynDB  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.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.esgyn.cnspark.apache.org/­sqltrafodion.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperDGraph LabsEsgynApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2017201520142014
Current release3.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen 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 languageGoC++, JavaScalaC++, Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesGoAll languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoJava Stored ProceduresnoJava Stored Procedures
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.nononono
User concepts infoAccess controlnofine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
BadgerEsgynDBSpark SQLTrafodion
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