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DBMS > GridDB vs. Microsoft Azure SQL Database vs. Prometheus vs. TimescaleDB

System Properties Comparison GridDB vs. Microsoft Azure SQL Database vs. Prometheus vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPrometheus  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataDatabase as a Service offering with high compatibility to Microsoft SQL ServerOpen-source Time Series DBMS and monitoring systemA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score78.40
Rank#15  Overall
#10  Relational DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitegriddb.netazure.microsoft.com/­en-us/­products/­azure-sql/­databaseprometheus.iowww.timescale.com
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­azure-sqlprometheus.io/­docsdocs.timescale.com
DeveloperToshiba CorporationMicrosoftTimescale
Initial release2013201020152017
Current release5.1, August 2022V122.13.0, November 2023
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 2.0
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++C++GoC
Server operating systemsLinuxhostedLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesNumeric data onlynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.noyesno infoImport of XML data possibleyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoTransact SQLnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availableyes infoby FederationSource-replica replication with hot standby and reads on replicas info
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 ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDnoACID
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.yesnono
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBMicrosoft Azure SQL Database infoformerly SQL AzurePrometheusTimescaleDB
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 SQL Database infoformerly SQL AzurePrometheusTimescaleDB
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Recent citations in the news

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16 January 2024, global.toshiba

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16 May 2023, global.toshiba

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1 November 2020, global.toshiba

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
3 December 2019, global.toshiba

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TimescaleDB Is a Vector Database Now, Too
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TimescaleDB for Azure Database for PostgreSQL to power IoT and time-series workloads | Azure updates
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