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DBMS > GridDB vs. Microsoft Azure Data Explorer

System Properties Comparison GridDB vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platform
Primary database modelTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsKey-value store
Relational DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.17
Rank#147  Overall
#11  Time Series DBMS
Score6.66
Rank#63  Overall
#36  Relational DBMS
Websitegriddb.netazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperToshiba CorporationMicrosoft
Initial release20132019
Current release5.1, August 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinuxhosted
Data schemeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyes
Secondary indexesyesall fields are automatically indexed
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, R
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAzure Active Directory Authentication
More information provided by the system vendor
GridDBMicrosoft Azure Data Explorer
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Azure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Kusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
IoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Microsoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsGitHub trending repository
» more
Azure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
An Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more

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