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DBMS > EsgynDB vs. Oracle Coherence vs. Spark SQL vs. Tkrzw

System Properties Comparison EsgynDB vs. Oracle Coherence vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonOracle Coherence  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 TrafodionOracles in-memory data grid solutionSpark 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 DBMSKey-value storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.97
Rank#129  Overall
#22  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.esgyn.cnwww.oracle.com/­java/­coherencespark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.oracle.com/­en/­middleware/­standalone/­coherencespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynOracleApache Software FoundationMikio Hirabayashi
Initial release2015200720142020
Current release14.1, August 20233.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen 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++, JavaJavaScalaC++
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeyesschema-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.nononono
Secondary indexesyesnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C++
Java
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnoyes infoLive Eventsnono
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 datacentersyes, with selectable consistency levelnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDconfigurableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infooptionallyyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infousing specific database classes
User concepts infoAccess controlfine grained access rights according to SQL-standardauthentification to access the cache via certificates or http basic authenticationnono

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More resources
EsgynDBOracle CoherenceSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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