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DBMS > Apache IoTDB vs. Machbase Neo vs. MaxDB vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison Apache IoTDB vs. Machbase Neo vs. MaxDB vs. Microsoft Azure Data Explorer vs. TimesTen

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  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 FlinkTimeSeries DBMS for AIoT and BigDataA robust and reliable RDBMS optimized to run all major SAP solutionsFully managed big data interactive analytics platformAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelTime Series DBMSTime Series DBMSRelational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.07
Rank#348  Overall
#34  Time Series DBMS
Score2.15
Rank#115  Overall
#55  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websiteiotdb.apache.orgmachbase.commaxdb.sap.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmachbase.com/­dbmsmaxdb.sap.com/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software FoundationMachbaseSAP, acquired from Software AG (Adabas-D) in 1997MicrosoftOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182013198420191998
Current release1.1.0, April 2023V8.0, August 20237.9.10.12, February 2024cloud service with continuous releasesRelease 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree test version availablecommercial infoLimited community edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Windows
AIX
HP-UX
Linux
Solaris
Windows
hostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
Native API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
ADO.NET
JDBC
ODBC
WebDAV
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
C#
Java
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyesnoyesYes, possible languages: KQL, Python, RPL/SQL
Triggersyesnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factorSource-replica replicationyes 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 SparknonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infovolatile and lookup tablenonoyes
User concepts infoAccess controlyessimple password-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Apache IoTDBMachbase Neo infoFormer name was InfinifluxMaxDB infoformerly named Adabas-DMicrosoft Azure Data ExplorerTimesTen
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