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DBMS > EJDB vs. Spark SQL vs. Transbase vs. Yanza

System Properties Comparison EJDB vs. Spark SQL vs. Transbase vs. Yanza

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSTime Series DBMS for IoT Applications
Primary database modelDocument storeRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#294  Overall
#44  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlyanza.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperSoftmotionsApache Software FoundationTransaction Software GmbHYanza
Initial release2012201419872015
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache 2.0commercial infofree development licensecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCScalaC and C++
Server operating systemsserver-lessLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyesno
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 indexesnonoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesno
APIs and other access methodsin-process shared libraryJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
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.nono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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More resources
EJDBSpark SQLTransbaseYanza
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