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DBMS > GridDB vs. HEAVY.AI vs. InfluxDB vs. MonetDB

System Properties Comparison GridDB vs. HEAVY.AI vs. InfluxDB vs. MonetDB

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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 comparisonInfluxDB  Xexclude from comparisonMonetDB  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 hardwareDBMS for storing time series, events and metricsA relational database management system that stores data in columns
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score22.12
Rank#28  Overall
#1  Time Series DBMS
Score1.72
Rank#135  Overall
#62  Relational DBMS
Websitegriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
www.influxdata.com/­products/­influxdb-overviewwww.monetdb.org
Technical documentationdocs.griddb.netdocs.heavy.aidocs.influxdata.com/­influxdbwww.monetdb.org/­Documentation
DeveloperToshiba CorporationHEAVY.AI, Inc.MonetDB BV
Initial release2013201620132004
Current release5.1, August 20225.10, January 20222.7.6, April 2024Dec2023 (11.49), December 2023
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 availableOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoMozilla Public License 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 CUDAGoC
Server operating systemsLinuxLinuxLinux
OS X infothrough Homebrew
FreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesNumeric data and Stringsyes
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.nonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query languageyes infoSQL 2003 with some extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
HTTP API
JSON over UDP
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnononoyes, in SQL, C, R
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoin enterprise version onlySharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationselectable replication factor infoin enterprise version onlynone infoSource-replica replication available in experimental status
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 Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonoACID
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 infoDepending on used storage engine
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardsimple rights management via user accountsfine 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 2022InfluxDBMonetDB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» 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 2022InfluxDBMonetDB
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Recent citations in the news

TOSHIBA DIGITAL SOLUTIONS CORPORATION
1 November 2020, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data Management
3 December 2019, global.toshiba

Amazon Proposes to Develop New Data Center Campus in Virginia
26 August 2022, w.media

’s SQL Interface, Aims to Accelerate Open Innovation
17 June 2020, global.toshiba

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5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

HEAVY.AI Accelerates Big Data Analytics with Vultr's High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

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Run and manage open source InfluxDB databases with Amazon Timestream
14 March 2024, AWS Blog

InfluxData avoids ’AI magic beans’ in InfluxDB time series database update for enterprises
4 September 2024, VentureBeat

InfluxData makes performance, storage improvements to InfluxDB 3.0
4 September 2024, InfoWorld

InfluxData's Latest Updates Optimize Time Series Data for Better Performance, Scale and Management
19 September 2024, Integration Developers

InfluxData Brings Higher Performance and New Features to InfluxDB 3.0 to Power Massive Time Series Workloads at Scale
4 September 2024, businesswire.com

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MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

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