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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTrino  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 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 platformFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Time Series 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
Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
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
Score5.00
Rank#66  Overall
#36  Relational DBMS
Websiteiotdb.apache.orgwww.graphengine.iomachbase.comazure.microsoft.com/­services/­data-explorertrino.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorertrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperApache Software FoundationMicrosoftMachbaseMicrosoftTrino Software Foundation
Initial release20182010201320192012 info2020 rebranded from PrestoSQL
Current release1.1.0, April 2023V8.0, August 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT Licensecommercial infofree test version availablecommercialOpen Source infoApache Version 2.0
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.
Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageJava.NET and CCJava
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinux
macOS
Windows
hostedLinux
macOS infofor devlopment
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 indexesyesyesall fields are automatically indexeddepending on connected data-source
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
Native API
RESTful HTTP APIgRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
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
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresyesyesnoYes, possible languages: KQL, Python, Ryes, depending on connected data-source
Triggersyesnonoyes 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)horizontal partitioningShardingSharding infoImplicit feature of the cloud servicedepending on connected data-source
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 factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.depending on connected data-source
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
depending on connected data-source
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononodepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storagenoyesdepending on connected data-source
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 controlyessimple password-based access controlAzure Active Directory AuthenticationSQL standard access control
More information provided by the system vendor
Apache IoTDBGraph Engine infoformer name: TrinityMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data ExplorerTrino
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
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