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DBMS > Apache Doris vs. Bangdb vs. Graphite vs. GridDB

System Properties Comparison Apache Doris vs. Bangdb vs. Graphite vs. GridDB

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonBangdb  Xexclude from comparisonGraphite  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolConverged and high performance database for device data, events, time series, document and graphData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Time Series DBMSTime Series DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Websitedoris.apache.org
github.com/­apache/­doris
bangdb.comgithub.com/­graphite-project/­graphite-webgriddb.net
Technical documentationgithub.com/­apache/­doris/­wikidocs.bangdb.comgraphite.readthedocs.iodocs.griddb.net
DeveloperApache Software Foundation, originally contributed from BaiduSachin Sinha, BangDBChris DavisToshiba Corporation
Initial release2017201220062013
Current release1.2.2, February 2023BangDB 2.0, October 20215.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3Open Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++PythonC++
Server operating systemsLinuxLinuxLinux
Unix
Linux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsNumeric data onlyyes infonumerical, string, blob, geometry, boolean, timestamp
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 indexesyesyes infosecondary, composite, nested, reverse, geospatialnoyes
SQL infoSupport of SQLyesSQL like support with command line toolnoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
MySQL client
Proprietary protocol
RESTful HTTP API
HTTP API
Sockets
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesJavaC
C#
C++
Java
Python
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersnoyes, Notifications (with Streaming only)noyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor, Knob for CAP (enterprise version only)noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglynoneImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyes infolockingyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modeyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes (enterprise version only)noAccess rights for users can be defined per database
More information provided by the system vendor
Apache DorisBangdbGraphiteGridDB
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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More resources
Apache DorisBangdbGraphiteGridDB
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Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
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How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
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Apache Doris just 'graduated': Why care about this SQL data warehouse
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8 May 2024, hackernoon.com

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