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GridDB System Properties

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Our visitors often compare GridDB with InfluxDB, TimescaleDB and DuckDB.

Editorial information provided by DB-Engines
DescriptionScalable in-memory time series database optimized for IoT and Big Data
Primary database modelTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Rank#142  Overall
#11  Time Series DBMS
Technical documentationdocs.griddb.net
DeveloperToshiba Corporation
Initial release2013
Current release5.1, August 2022
License infoCommercial or Open SourceOpen 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 serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinux
Data schemeyes
Typing infopredefined data types such as float or dateyes 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.no
Secondary indexesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
Proprietary protocol
Supported programming languagesC
JavaScript (Node.js)
Server-side scripts infoStored proceduresno
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container level
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users can be defined per database
More information provided by the system vendor
Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and Big Data. Its in-memory data architecture coupled with parallel processing technology makes GridDB faster than any other time series databases. GridDB's Key-Container data model is designed from the ground up to handle IoT/Time-series data model. Visit GitHub and Developer site for more information:
GridDB Open Source
GridDB developer site

Competitive advantages

1. Optimized for IoT
Equipped with Toshiba's proprietary key-container data model that guarantees ACID compliance at the container level, provides time-series functionalities, and presents excellent performance. 
2. High Performance
In-memory architecture with a superb parallel processing and minimal overhead. Fast ingest and query for various types of data structures.
3. High Scalability
Scale out to 1,000 nodes with commodity hardware. 
4. High Availability
GridDB's Hybrid Architecture eliminates Single Point of Failure. 

[see article]

Benchmark Results:

GridDB vs MariaDB

GridDB vs InfluxDB

GridDB vs Cassandra

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.

Key customers
  • Denso International [see use case]
  • An Electric Power company [see use case]
  • Ishinomaki City Smart Community Project
  • Kobe Steel.
Market metrics

GitHub trending repository

Licensing and pricing models
  • Open Source license (AGPL v3 & Apache v2)
  • Commercial license (subscription)

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Recent citations in the news

Snowflake targets Java and Scala devs, will soon slither after Pythonistas too
8 June 2021, The Register

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