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DBMS > Microsoft Azure Data Explorer vs. MonetDB vs. mSQL vs. MySQL vs. TypeDB

System Properties Comparison Microsoft Azure Data Explorer vs. MonetDB vs. mSQL vs. MySQL vs. TypeDB

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMonetDB  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonMySQL  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA relational database management system that stores data in columnsmSQL (Mini SQL) is a simple and lightweight RDBMSWidely used open source RDBMSTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelRelational DBMS infocolumn orientedRelational DBMSRelational DBMSRelational DBMS infoKey/Value like access via memcached APIGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Secondary database modelsDocument 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
Document store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score1.72
Rank#148  Overall
#68  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score1087.72
Rank#2  Overall
#2  Relational DBMS
Score0.81
Rank#217  Overall
#19  Graph DBMS
#99  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.monetdb.orghughestech.com.au/­products/­msqlwww.mysql.comtypedb.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.monetdb.org/­Documentationdev.mysql.com/­doctypedb.com/­docs
DeveloperMicrosoftMonetDB BVHughes TechnologiesOracle infosince 2010, originally MySQL AB, then SunVaticle
Initial release20192004199419952016
Current releasecloud service with continuous releasesDec2023 (11.49), December 20234.4, October 20218.3.0, January 20242.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoMozilla Public License 2.0commercial infofree licenses can be providedOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageCCC and C++Java
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)yesyesyesyes
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyesyes
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.yesnoyesno
Secondary indexesall fields are automatically indexedyesyesyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes infoSQL 2003 with some extensionsA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersyes infowith proprietary extensionsno
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C++
Delphi
Java
Perl
PHP
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes, in SQL, C, Rnoyes infoproprietary syntaxno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding via remote tablesnonehorizontal partitioning, sharding with MySQL Cluster or MySQL FabricSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none infoSource-replica replication available in experimental statusnoneMulti-source replication
Source-replica replication
Multi-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknononoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
noneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engineno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes infotable locks or row locks depending on storage engineyes
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.nonoyesno
User concepts infoAccess controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept infono user groups or rolesyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Microsoft Azure Data ExplorerMonetDBmSQL infoMini SQLMySQLTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Microsoft Azure Data ExplorerMonetDBmSQL infoMini SQLMySQLTypeDB infoformerly named Grakn
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