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DBMS > GridDB vs. Microsoft Azure Data Explorer vs. Prometheus vs. Solr

System Properties Comparison GridDB vs. Microsoft Azure Data Explorer vs. Prometheus vs. Solr

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPrometheus  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformOpen-source Time Series DBMS and monitoring systemA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedTime Series DBMSSearch engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitegriddb.netazure.microsoft.com/­services/­data-explorerprometheus.iosolr.apache.org
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerprometheus.io/­docssolr.apache.org/­resources.html
DeveloperToshiba CorporationMicrosoftApache Software Foundation
Initial release2013201920152006
Current release5.1, August 2022cloud service with continuous releases9.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJava
Server operating systemsLinuxhostedLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyes infoDynamic Fields enables on-the-fly addition of new fields
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-typesNumeric data onlyyes infosupports customizable data types and automatic typing
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.noyesno infoImport of XML data possibleyes
Secondary indexesyesall fields are automatically indexednoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP/JSON APIJava API
RESTful HTTP/JSON API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RnoJava plugins
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
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.yes infoby Federationyes
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-sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
noneEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonooptimistic locking
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.yesnonoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAzure Active Directory Authenticationnoyes
More information provided by the system vendor
GridDBMicrosoft Azure Data ExplorerPrometheusSolr
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» 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
GridDBMicrosoft Azure Data ExplorerPrometheusSolr
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