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DBMS > Oracle Berkeley DB vs. Oracle Coherence vs. OrigoDB vs. Spark SQL vs. Transbase

System Properties Comparison Oracle Berkeley DB vs. Oracle Coherence vs. OrigoDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameOracle Berkeley DB  Xexclude from comparisonOracle Coherence  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionWidely used in-process key-value storeOracles in-memory data grid solutionA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Key-value storeDocument store
Object oriented DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score1.97
Rank#129  Overall
#22  Key-value stores
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.oracle.com/­java/­coherenceorigodb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmldocs.oracle.com/­en/­middleware/­standalone/­coherenceorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OracleOracleRobert Friberg et alApache Software FoundationTransaction Software GmbH
Initial release199420072009 infounder the name LiveDB20141987
Current release18.1.40, May 202014.1, August 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infocommercial license availablecommercialOpen SourceOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)JavaC#ScalaC and C++
Server operating systemsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
All OS with a Java VMLinux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesUser defined using .NET types and collectionsyesyes
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.yes infoonly with the Berkeley DB XML editionnono infocan be achieved using .NETnono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyes infoSQL interfaced based on SQLite is availablenonoSQL-like DML and DDL statementsyes
APIs and other access methodsJCache
JPA
RESTful HTTP API
.NET Client API
HTTP API
LINQ
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C++
Java
.NetJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyesnoyes
Triggersyes infoonly for the SQL APIyes infoLive Eventsyes infoDomain Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with selectable consistency levelSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonodepending on modelnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDconfigurableACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infooptionallyyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnono
User concepts infoAccess controlnoauthentification to access the cache via certificates or http basic authenticationRole based authorizationnofine grained access rights according to SQL-standard

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More resources
Oracle Berkeley DBOracle CoherenceOrigoDBSpark SQLTransbase
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