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DBMS > Apache IoTDB vs. BaseX vs. Graph Engine vs. Microsoft Azure Data Explorer vs. TDSQL for MySQL

System Properties Comparison Apache IoTDB vs. BaseX vs. Graph Engine vs. Microsoft Azure Data Explorer vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBaseX  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTDSQL for MySQL  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 FlinkLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelTime Series DBMSNative XML DBMSGraph DBMS
Key-value store
Relational 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websiteiotdb.apache.orgbasex.orgwww.graphengine.ioazure.microsoft.com/­services/­data-explorerwww.tencentcloud.com/­products/­dcdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.basex.orgwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tencentcloud.com/­document/­product/­1042
DeveloperApache Software FoundationBaseX GmbHMicrosoftMicrosoftTencent
Initial release20182007201020192013
Current release1.1.0, April 202310.7, August 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD licenseOpen Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava.NET and C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
.NEThostedhosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyesyes 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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenonoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyesyesYes, possible languages: KQL, Python, Ryes
Triggersyesyes infovia eventsnoyes 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)nonehorizontal partitioningSharding infoImplicit feature of the cloud serviceAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoSpark 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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writernonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlyesUsers with fine-grained authorization concept on 4 levelsAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
Apache IoTDBBaseXGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerTDSQL for MySQL
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