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DBMS > Apache IoTDB vs. Dragonfly vs. Graph Engine vs. Machbase Neo vs. Microsoft Azure Data Explorer

System Properties Comparison Apache IoTDB vs. Dragonfly vs. Graph Engine vs. Machbase Neo vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDragonfly  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineTimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platform
Primary database modelTime Series DBMSKey-value storeGraph DBMS
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
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteiotdb.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.graphengine.iomachbase.comazure.microsoft.com/­services/­data-explorer
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.dragonflydb.io/­docswww.graphengine.io/­docs/­manualmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationDragonflyDB team and community contributorsMicrosoftMachbaseMicrosoft
Initial release20182023201020132019
Current release1.1.0, April 20231.0, March 2023V8.0, August 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSL 1.1Open Source infoMIT Licensecommercial infofree test version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++.NET and CC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux.NETLinux
macOS
Windows
hosted
Data schemeyesscheme-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyesyes 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.nonononoyes
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Native API
Proprietary protocol infoRESP - REdis Serialization ProtocolRESTful HTTP APIgRPC
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
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
F#
Visual Basic
C
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 proceduresyesLuayesnoYes, possible languages: KQL, Python, R
Triggersyespublish/subscribe channels provide some trigger functionalitynonoyes 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)horizontal partitioningShardingSharding 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 replicasSource-replica replicationselectable 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 SparknonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsnonono
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
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 storagenoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infovolatile and lookup tableno
User concepts infoAccess controlyesPassword-based authenticationsimple password-based access controlAzure Active Directory Authentication

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More resources
Apache IoTDBDragonflyGraph Engine infoformer name: TrinityMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data Explorer
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