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DBMS > Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL vs. Trino

System Properties Comparison Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL vs. Trino

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMongoDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational DBMS infocolumn orientedDocument storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational 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
Spatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.00
Rank#66  Overall
#36  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.mongodb.comwww.postgresql.orgtrino.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.mongodb.com/­docs/­manualwww.postgresql.org/­docstrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperMicrosoftMongoDB, IncPostgreSQL Global Development Group infowww.postgresql.org/­developerTrino Software Foundation
Initial release201920091989 info1989: Postgres, 1996: PostgreSQL2012 info2020 rebranded from PrestoSQL
Current releasecloud service with continuous releases6.0.7, June 202316.2, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoBSDOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesno infoMongoDB available as DBaaS (MongoDB Atlas)nono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageC++CJava
Server operating systemshostedLinux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
macOS infofor devlopment
Data schemeFixed schema with schema-less datatypes (dynamic)schema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.yesyes
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 infostring, integer, double, decimal, boolean, date, object_id, geospatialyesyes
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.yesyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesall fields are automatically indexedyesyesdepending on connected data-source
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetRead-only SQL queries via the MongoDB Atlas SQL Interfaceyes infostandard with numerous extensionsyes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
RESTful HTTP API
Trino CLI
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RJavaScriptuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes, depending on connected data-source
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoin MongoDB Atlas onlyyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.partitioning by range, list and (since PostgreSQL 11) by hashdepending 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.Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsdepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate Consistencydepending on connected data-source
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-document ACID Transactions with snapshot isolationACIDdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infooptional, enabled by defaultyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standardSQL standard access control
More information provided by the system vendor
Microsoft Azure Data ExplorerMongoDBPostgreSQLTrino
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Trino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Trino is widely adopted across the globe as freely-available open source software....
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more
Trino is an open source project and usage is therefore free. Commercial offerings...
» more
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We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
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DB-Engines blog posts

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Conferences, events and webinars

Intro to MongoDB
Webinar, 11am ET, 1 May 2024 (finished)

Monitoring PostgreSQL with Redgate Monitor
Webinar, 10-11am CT / 4-5pm BST, 22 May 2024

Recent citations in the news

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, azure.microsoft.com

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