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DBMS > Apache IoTDB vs. Microsoft Azure Data Explorer vs. MySQL vs. OrigoDB vs. SAP Advantage Database Server

System Properties Comparison Apache IoTDB vs. Microsoft Azure Data Explorer vs. MySQL vs. OrigoDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMySQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonSAP Advantage Database Server infoformer name: Sybase ADS  Xexclude from comparison
SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkFully managed big data interactive analytics platformWidely used open source RDBMSA fully ACID in-memory object graph databaseLow-cost RDBMS with access to ISAM and FoxPro data structures
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRelational DBMS infoKey/Value like access via memcached APIDocument store
Object oriented DBMS
Relational DBMS
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­services/­data-explorerwww.mysql.comorigodb.comwww.sap.com/products/advantage-database-server.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdev.mysql.com/­docorigodb.com/­docs
DeveloperApache Software FoundationMicrosoftOracle infosince 2010, originally MySQL AB, then SunRobert Friberg et alSybase, SAP
Initial release2018201919952009 infounder the name LiveDB1993
Current release1.1.0, April 2023cloud service with continuous releases8.4.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Sourcecommercial
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.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageJavaC and C++C#
Server operating systemsAll OS with a Java VM (>= 1.8)hostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
Windows
Linux
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesUser defined using .NET types and collectionsyes
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.noyesyesno infocan be achieved using .NETno
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsnoyes
APIs and other access methodsJDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
.NET Client API
HTTP API
LINQ
.NET Client API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.NetDelphi
Perl
PHP
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ryes infoproprietary syntaxyesyes
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud servicehorizontal partitioning, sharding with MySQL Cluster or MySQL Fabrichorizontal partitioning infoclient side managed; servers are not synchronizednone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Source-replica replicationMulti-source replication infoCONFLICT Trigger to resolve replication conflicts
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage enginedepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infonot for MyISAM storage engineACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesno infocaching of (temporary) tables can be configured
User concepts infoAccess controlyesAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or rolesRole based authorizationfine grained access rights according to SQL-standard

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More resources
Apache IoTDBMicrosoft Azure Data ExplorerMySQLOrigoDBSAP Advantage Database Server infoformer name: Sybase ADS
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