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DBMS > BigchainDB vs. Oracle Berkeley DB vs. Spark SQL vs. Sphinx vs. Transbase

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

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsWidely 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 resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.bigchaindb.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlsphinxsearch.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.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.Transaction Software GmbH
Initial release20161994201420011987
Current release18.1.40, May 20203.5.0 ( 2.13), September 20233.5.1, February 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial 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 languagePythonC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C and C++
Server operating systemsLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenonoyesnoyes
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 editionnono
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsCLI Client
RESTful HTTP API
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.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++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnononoyes
Triggersyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonononoyes
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 persistentyes,with MongoDB ord RethinkDByesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesnononofine grained access rights according to SQL-standard

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More resources
BigchainDBOracle Berkeley DBSpark SQLSphinxTransbase
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