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DBMS > Bangdb vs. GeoMesa vs. GridDB vs. QuestDB

System Properties Comparison Bangdb vs. GeoMesa vs. GridDB vs. QuestDB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGeoMesa  Xexclude from comparisonGridDB  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Scalable in-memory time series database optimized for IoT and Big DataA high performance open source SQL database for time series data
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Spatial DBMSTime Series DBMSTime Series DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
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
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitebangdb.comwww.geomesa.orggriddb.netquestdb.io
Technical documentationdocs.bangdb.comwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.griddb.netquestdb.io/­docs
DeveloperSachin Sinha, BangDBCCRi and othersToshiba CorporationQuestDB Technology Inc
Initial release2012201420132014
Current releaseBangDB 2.0, October 20215.0.0, May 20245.1, August 2022
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache License 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaC++Java (Zero-GC), C++, Rust
Server operating systemsLinuxLinuxLinux
macOS
Windows
Data schemeschema-freeyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL like support with command line toolnoSQL92, SQL-like TQL (Toshiba Query Language)SQL with time-series extensions
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnononono
Triggersyes, Notifications (with Streaming only)noyesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmdepending on storage layerShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)depending on storage layerSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglydepending on storage layerImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container levelACID for single-table writes
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 modedepending on storage layeryesyes infothrough memory mapped files
User concepts infoAccess controlyes (enterprise version only)yes infodepending on the DBMS used for storageAccess rights for users can be defined per database
More information provided by the system vendor
BangdbGeoMesaGridDBQuestDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
BangdbGeoMesaGridDBQuestDB
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