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DBMS > DataFS vs. Microsoft Azure Data Explorer vs. MongoDB vs. openGauss vs. QuestDB

System Properties Comparison DataFS vs. Microsoft Azure Data Explorer vs. MongoDB vs. openGauss vs. QuestDB

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMongoDB  Xexclude from comparisonopenGauss  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Fully 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 infrastructureAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiA high performance open source SQL database for time series data
Primary database modelObject oriented DBMSRelational DBMS infocolumn orientedDocument storeRelational DBMSTime Series DBMS
Secondary database modelsGraph DBMSDocument 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
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score1.08
Rank#183  Overall
#84  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitenewdatabase.comazure.microsoft.com/­services/­data-explorerwww.mongodb.comgitee.com/­opengauss
opengauss.org
questdb.io
Technical documentationdev.mobiland.com/­Overview.xspdocs.microsoft.com/­en-us/­azure/­data-explorerwww.mongodb.com/­docs/­manualdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
questdb.io/­docs
DeveloperMobiland AGMicrosoftMongoDB, IncHuawei and openGauss communityQuestDB Technology Inc
Initial release20182019200920192014
Current release1.1.263, October 2022cloud service with continuous releases6.0.7, June 20233.0, March 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno 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.
Implementation languageC++C, C++, JavaJava (Zero-GC), C++, Rust
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
LinuxLinux
macOS
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)Fixed 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 infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyes 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.noyesnono
Secondary indexesnoall fields are automatically indexedyesyesno
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetRead-only SQL queries via the MongoDB Atlas SQL InterfaceANSI SQL 2011SQL with time-series extensions
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languages.Net
C
C#
C++
VB.Net
.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
C
C++
Java
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RJavaScriptyesno
Triggersno, except callback-events from server when changes happenedyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoin MongoDB Atlas onlyyesno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemSharding 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.horizontal partitioning (by range, list and hash)horizontal partitioning (by timestamps)
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 replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoMulti-document ACID Transactions with snapshot isolationACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by defaultyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoIn-memory storage engine introduced with MongoDB version 3.2noyes infothrough memory mapped files
User concepts infoAccess controlWindows-ProfileAzure Active Directory AuthenticationAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DataFSMicrosoft Azure Data ExplorerMongoDBopenGaussQuestDB
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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