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DBMS > Bangdb vs. EsgynDB vs. GridDB vs. Solr

System Properties Comparison Bangdb vs. EsgynDB vs. GridDB vs. Solr

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable in-memory time series database optimized for IoT and Big DataA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSTime Series DBMSSearch engine
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
Spatial 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
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitebangdb.comwww.esgyn.cngriddb.netsolr.apache.org
Technical documentationdocs.bangdb.comdocs.griddb.netsolr.apache.org/­resources.html
DeveloperSachin Sinha, BangDBEsgynToshiba CorporationApache Software Foundation
Initial release2012201520132006
Current releaseBangDB 2.0, October 20215.1, August 20229.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2
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++, JavaC++Java
Server operating systemsLinuxLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes infonumerical, string, blob, geometry, boolean, timestampyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL like support with command line toolyesSQL92, SQL-like TQL (Toshiba Query Language)Solr Parallel SQL Interface
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
Python
All languages supporting JDBC/ODBC/ADO.NetC
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
Server-side scripts infoStored proceduresnoJava Stored ProceduresnoJava plugins
Triggersyes, Notifications (with Streaming only)noyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication between multi datacentersSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container leveloptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
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 modenoyesyes
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardAccess rights for users can be defined per databaseyes
More information provided by the system vendor
BangdbEsgynDBGridDBSolr
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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BangdbEsgynDBGridDBSolr
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