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DBMS > GridDB vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. StarRocks vs. TimescaleDB

System Properties Comparison GridDB vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. StarRocks vs. TimescaleDB

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSequoiadb  Xexclude from comparisonStarRocks  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformNewSQL database with distributed OLTP and SQLAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache DorisA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedDocument store
Relational DBMS
Relational DBMSTime Series DBMS
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score1.04
Rank#189  Overall
#88  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitegriddb.netazure.microsoft.com/­services/­data-explorerwww.sequoiadb.comwww.starrocks.iowww.timescale.com
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sequoiadb.com/­en/­index.php?m=Files&a=indexdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_introdocs.timescale.com
DeveloperToshiba CorporationMicrosoftSequoiadb Ltd.The Linux Foundation infosince Feb 2023Timescale
Initial release20132019201320202017
Current release5.1, August 2022cloud service with continuous releases2.5.3, March 20232.15.0, 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 infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++, JavaC
Server operating systemsLinuxhostedLinuxLinuxLinux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesyes
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-typesyes infooid, date, timestamp, binary, regexyesnumerics, 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.noyesnonoyes
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetSQL-like query languageyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSONJDBC
MySQL protocol
ADO.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
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
PHP
Python
Java.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RJavaScriptuser defined functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning (by range and hash)yes, across time and space (hash partitioning) attributes
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.Source-replica replicationSource-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 jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoDocument is locked during a transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononono
User concepts infoAccess controlAccess rights for users can be defined per databaseAzure Active Directory Authenticationsimple password-based access controlRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBMicrosoft Azure Data ExplorerSequoiadbStarRocksTimescaleDB
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 ExplorerSequoiadbStarRocksTimescaleDB
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