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DBMS > GridDB vs. Hawkular Metrics vs. MongoDB

System Properties Comparison GridDB vs. Hawkular Metrics vs. MongoDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelTime Series DBMSTime Series DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.37
Rank#142  Overall
#11  Time Series DBMS
Score0.24
Rank#360  Overall
#35  Time Series DBMS
Score436.61
Rank#5  Overall
#1  Document stores
Websitegriddb.netwww.hawkular.orgwww.mongodb.com
Technical documentationdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.mongodb.com/­manual
DeveloperToshiba CorporationCommunity supported by Red HatMongoDB, Inc
Initial release201320142009
Current release5.1, August 20226.0.5, March 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 2.0Open Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • ScaleGrid for MongoDB Database: Fully managed hosting for MongoDB Database on a wide variety of cloud providers and On-Premises. Automate your management, scaling and backups through one centralized platform.
  • MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
Implementation languageC++JavaC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTproprietary protocol using JSON
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
Server-side scripts infoStored proceduresnonoJavaScript
Triggersyesyes infovia Hawkular Alertingyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandraMulti-Source deployments with MongoDB Atlas Global Clusters
Source-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 jobsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by default
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlAccess rights for users can be defined per databasenoAccess rights for users and roles
More information provided by the system vendor
GridDBHawkular MetricsMongoDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Built around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Internet of Things and Time Series (Bosch, GE Healthcare, Jaguar Land Rover) Mobile...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsGitHub trending repository
» more
365+ million downloads, over 150,000+ Atlas clusters provisioned every month handling...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
GridDBHawkular MetricsMongoDB
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