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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. Machbase Neo vs. Microsoft Azure Data Explorer

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. Machbase Neo vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed 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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksTimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platform
Primary database modelTime Series DBMSDocument store
Key-value store
Time Series DBMSRelational DBMS infocolumn oriented
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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorymachbase.comazure.microsoft.com/­services/­data-explorer
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationAtos Convergence CreatorsMachbaseMicrosoft
Initial release2018201620132019
Current release1.1.0, April 20231703V8.0, August 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree test version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Windows
hosted
Data schemeyesSchema and schema-less with LDAP viewsyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesoptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyesnoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Native API
LDAPgRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnonoYes, possible languages: KQL, Python, R
Triggersyesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesselectable replication factoryes 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 SparknoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infovolatile and lookup tableno
User concepts infoAccess controlyesLDAP bind authenticationsimple password-based access controlAzure Active Directory Authentication

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More resources
Apache IoTDBAtos Standard Common RepositoryMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data Explorer
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