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DBMS > Bangdb vs. GridDB vs. Sphinx vs. VelocityDB

System Properties Comparison Bangdb vs. GridDB vs. Sphinx vs. VelocityDB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphScalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databasesA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Time Series DBMSSearch engineGraph DBMS
Object oriented DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.11
Rank#354  Overall
#37  Graph DBMS
#15  Object oriented DBMS
Websitebangdb.comgriddb.netsphinxsearch.comvelocitydb.com
Technical documentationdocs.bangdb.comdocs.griddb.netsphinxsearch.com/­docsvelocitydb.com/­UserGuide
DeveloperSachin Sinha, BangDBToshiba CorporationSphinx Technologies Inc.VelocityDB Inc
Initial release2012201320012011
Current releaseBangDB 2.0, October 20215.1, August 20223.5.1, February 20237.x
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence availablecommercial
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++C#
Server operating systemsLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Any that supports .NET
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes infonumerical, string, blob, geometry, boolean, timestampnoyes
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.nonono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL like support with command line toolSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)no
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol.Net
Supported programming languagesC
C#
C++
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
Server-side scripts infoStored proceduresnononono
Triggersyes, Notifications (with Streaming only)yesnoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyes 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.yes, run db with in-memory only modeyesyes
User concepts infoAccess controlyes (enterprise version only)Access rights for users can be defined per databasenoBased on Windows Authentication
More information provided by the system vendor
BangdbGridDBSphinxVelocityDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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BangdbGridDBSphinxVelocityDB
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