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DBMS > GridDB vs. HEAVY.AI vs. Kingbase vs. QuestDB

System Properties Comparison GridDB vs. HEAVY.AI vs. Kingbase vs. QuestDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKingbase  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.A high performance open source SQL database for time series data
Primary database modelTime Series DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitegriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kingbase.com.cnquestdb.io
Technical documentationdocs.griddb.netdocs.heavy.aiquestdb.io/­docs
DeveloperToshiba CorporationHEAVY.AI, Inc.BeiJing KINGBASE Information technologies inc.QuestDB Technology Inc
Initial release2013201619992014
Current release5.1, August 20225.10, January 2022V8.0, August 2021
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ and CUDAC and JavaJava (Zero-GC), C++, Rust
Server operating systemsLinuxLinuxLinux
Windows
Linux
macOS
Windows
Data schemeyesyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.nonoyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesStandard with numerous extensionsSQL with time-series extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinhorizontal partitioning (by range, list and hash) and vertical partitioninghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationyesSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KingbaseQuestDB
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
GridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KingbaseQuestDB
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