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DBMS > EsgynDB vs. OpenTenBase vs. Spark SQL vs. Tkrzw

System Properties Comparison EsgynDB vs. OpenTenBase vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonOpenTenBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAn enterprise-level distributed HTAP open source database based on PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.08
Rank#370  Overall
#156  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.esgyn.cngithub.com/­OpenTenBase/­OpenTenBase
www.opentenbase.org
spark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.opentenbase.org
docs.opentenbase.org/­en
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynOpenAtom Foundation, previously TencentApache Software FoundationMikio Hirabayashi
Initial release201520142020
Current release2.5, January 20243.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaScalaC++
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
macOS
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesno
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
Go
Java
PHP
Python
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Proceduresnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.nonoyes infousing specific database classes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardnono

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More resources
EsgynDBOpenTenBaseSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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