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

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

Editorial information provided by DB-Engines
NameOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesA high performance, scalable Wide Column DBMSA 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
Relational DBMSSearch engineWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.01
Rank#387  Overall
#13  Wide column stores
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlsphinxsearch.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationSphinx Technologies Inc.Alex KashirinTransaction Software GmbH
Initial release19942014200120201987
Current release18.1.40, May 20203.5.0 ( 2.13), September 20233.5.1, February 20230.5, April 2021Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C++C and C++
Server operating systemsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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 editionnonono
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language (SphinxQL)SQL-like query languageyes
APIs and other access methodsJDBC
ODBC
Proprietary protocolProprietary protocol
Thrift
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
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonononoyes
Triggersyes infoonly for the SQL APInononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneSource-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 integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlnononofine grained access rights according to SQL-standard

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More resources
Oracle Berkeley DBSpark SQLSphinxSWC-DB infoSuper Wide Column DatabaseTransbase
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