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DBMS > Apache IoTDB vs. Microsoft Azure Data Explorer vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. Microsoft Azure Data Explorer vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparison
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 platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRelational 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
Score1.13
Rank#199  Overall
#16  Time Series DBMS
Score6.47
Rank#62  Overall
#36  Relational DBMS
Score0.52
Rank#267  Overall
#121  Relational DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­services/­data-explorerwww.postgres-xl.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationMicrosoft
Initial release201820192014 infosince 2012, originally named StormDB
Current release1.1.0, April 2023cloud service with continuous releases10 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
macOS
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes
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-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.noyesyes infoXML type, but no XML query functionality
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ruser defined functions
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
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
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBMicrosoft Azure Data ExplorerPostgres-XL
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more
Licensing and pricing modelsAn Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more

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Apache IoTDBMicrosoft Azure Data ExplorerPostgres-XL
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