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DBMS > Lovefield vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. Transbase

System Properties Comparison Lovefield vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB vs. Transbase

Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionEmbeddable relational database for web apps written in pure JavaScriptWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#387  Overall
#13  Wide column stores
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitegoogle.github.io/­lovefieldwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.transaction.de/­en/­products/­transbase.html
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex KashirinTransaction Software GmbH
Initial release20141994201420201987
Current release2.1.12, February 201718.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 2021Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3commercial 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 languageJavaScriptC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and C++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
LinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.noyes infoonly with the Berkeley DB XML editionnonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJavaScript.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
Java
Python
R
Scala
C++C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonononoyes
TriggersUsing read-only observersyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDByesnonono
User concepts infoAccess controlnononofine grained access rights according to SQL-standard

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More resources
LovefieldOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column DatabaseTransbase
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