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DBMS > Apache IoTDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Prometheus

System Properties Comparison Apache IoTDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Prometheus

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonPrometheus  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 FlinkA widely adopted in-memory data gridFully managed big data interactive analytics platformLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsOpen-source Time Series DBMS and monitoring system
Primary database modelTime Series DBMSKey-value storeRelational DBMS infocolumn orientedObject oriented DBMS
Vector DBMS
Time Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.08
Rank#179  Overall
#6  Object oriented DBMS
#9  Vector DBMS
Score7.56
Rank#49  Overall
#3  Time Series DBMS
Websiteiotdb.apache.orghazelcast.comazure.microsoft.com/­services/­data-explorergithub.com/­objectbox
objectbox.io
prometheus.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.ioprometheus.io/­docs
DeveloperApache Software FoundationHazelcastMicrosoftObjectBox Limited
Initial release20182008201920172015
Current release1.1.0, April 20235.3.6, November 2023cloud service with continuous releases4.0 (May 2024)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercialBindings are released under Apache 2.0 infoApache License 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++Go
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMhostedAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Linux
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes, plus "flex" map-like typesNumeric data only
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.noyes infothe object must implement a serialization strategyyesnono infoImport of XML data possible
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languageKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIRESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rnono
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoImplicit feature of the cloud servicenoneSharding
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 infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Data sync between devices allowing occasional connected databases to work completely offlineyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistencynone
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonono
User concepts infoAccess controlyesRole-based access controlAzure Active Directory Authenticationyesno
More information provided by the system vendor
Apache IoTDBHazelcastMicrosoft Azure Data ExplorerObjectBoxPrometheus
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