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DBMS > Microsoft Azure Data Explorer vs. Trino

System Properties Comparison Microsoft Azure Data Explorer vs. Trino

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Our visitors often compare Microsoft Azure Data Explorer and Trino with Databricks, Elasticsearch and ClickHouse.

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational 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
Score2.94
Rank#85  Overall
#46  Relational DBMS
Score5.18
Rank#60  Overall
#34  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorertrino.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorertrino.io/­broadcast
trino.io/­docs/­current
DeveloperMicrosoftTrino Software Foundation
Initial release20192012 info2020 rebranded from PrestoSQL
Current releasecloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedLinux
macOS infofor devlopment
Data schemeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes 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.yesno
Secondary indexesall fields are automatically indexeddepending on connected data-source
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
RESTful HTTP API
Trino CLI
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes, depending on connected data-source
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicedepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesyes 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 methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
depending on connected data-source
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanodepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAzure Active Directory AuthenticationSQL standard access control
More information provided by the system vendor
Microsoft Azure Data ExplorerTrino
News

73: Wrapping Trino packages with a bow
9 April 2025

Core Principles and Design Practices of OLAP Engines
27 March 2025

72: Keeping the lake clean
17 March 2025

Twenty four
3 March 2025

71: Fake it real good
27 February 2025

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More resources
Microsoft Azure Data ExplorerTrino
Recent citations in the news

Universal Destinations & Experiences proactively improves guest satisfaction with Azure Data Explorer
14 February 2025, Microsoft

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft Azure

Azure Data Explorer Supports Native Ingestion from Amazon S3
7 September 2022, infoq.com

Microsoft announces general availability of Azure Data Explorer and Azure Data Lake Storage Gen2
7 February 2019, VentureBeat

provided by Google News

The Perfect AI Storage: Trino From Facebook And Iceberg From Netflix?
30 April 2024, The Next Platform

How to Deploy MinIO and Trino with Kubernetes
23 May 2024, HackerNoon

A look at Presto, Trino SQL query engines
9 August 2022, TechTarget

Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost
4 October 2023, Amazon Web Services (AWS)

Trino turns 10: Starburst celebrates a decade of its open source query engine
11 August 2022, VentureBeat

provided by Google News



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