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DBMS > Alibaba Cloud AnalyticDB for MySQL vs. GridDB vs. Microsoft Azure Data Explorer vs. TimescaleDB vs. Transbase

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. GridDB vs. Microsoft Azure Data Explorer vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
NameAlibaba Cloud AnalyticDB for MySQL  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.Scalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-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
Score0.91
Rank#201  Overall
#94  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.alibabacloud.com/­product/­analyticdb-for-mysqlgriddb.netazure.microsoft.com/­services/­data-explorerwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationwww.alibabacloud.com/­help/­doc-detail/­93776.htmdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperAlibabaToshiba CorporationMicrosoftTimescaleTransaction Software GmbH
Initial release2013201920171987
Current release5.1, August 2022cloud service with continuous releases2.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC and C++
Server operating systemshostedLinuxhostedLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes 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-typesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.yesnoyesyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnoACIDyes
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.yesyesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
Alibaba Cloud AnalyticDB for MySQLGridDBMicrosoft Azure Data ExplorerTimescaleDBTransbase
Specific characteristicsA real-time data warehousing service that can process PB data with high concurrency...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesTPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
» more
1. 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 modelsAvailable regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Alibaba Cloud AnalyticDB for MySQLGridDBMicrosoft Azure Data ExplorerTimescaleDBTransbase
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