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DBMS > Bangdb vs. Cubrid vs. Solr vs. Sphinx

System Properties Comparison Bangdb vs. Cubrid vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonCubrid  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSSearch engineSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitebangdb.comcubrid.com (korean)
cubrid.org (english)
solr.apache.orgsphinxsearch.com
Technical documentationdocs.bangdb.comcubrid.org/­manualssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperSachin Sinha, BangDBCUBRID Corporation, CUBRID FoundationApache Software FoundationSphinx Technologies Inc.
Initial release2012200820062001
Current releaseBangDB 2.0, October 202111.0, January 20219.5.0, February 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C, C++, JavaJavaC++
Server operating systemsLinuxLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes infosupports customizable data types and automatic typingno
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.nonoyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL like support with command line toolyesSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC
C#
C++
Java
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava Stored ProceduresJava pluginsno
Triggersyes, Notifications (with Streaming only)yesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenoyes
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardyesno

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BangdbCubridSolrSphinx
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