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DBMS > Microsoft Azure Data Explorer vs. PlanetScale vs. Prometheus vs. Sphinx

System Properties Comparison Microsoft Azure Data Explorer vs. PlanetScale vs. Prometheus vs. Sphinx

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonPlanetScale  Xexclude from comparisonPrometheus  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformScalable, distributed, serverless MySQL database platform built on top of VitessOpen-source Time Series DBMS and monitoring systemOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS infocolumn orientedRelational DBMSTime Series DBMSSearch engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteazure.microsoft.com/­services/­data-explorerplanetscale.comprometheus.iosphinxsearch.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerplanetscale.com/­docsprometheus.io/­docssphinxsearch.com/­docs
DeveloperMicrosoftPlanetScaleSphinx Technologies Inc.
Initial release2019202020152001
Current releasecloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoC++
Server operating systemshostedDocker
Linux
macOS
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)yesyesyes
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-typesyesNumeric data onlyno
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 infoImport of XML data possible
Secondary indexesall fields are automatically indexedyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsnoSQL-like query language (SphinxQL)
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
RESTful HTTP/JSON APIProprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes infoproprietary syntaxnono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
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 replication
Source-replica replication
yes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
none
Foreign keys infoReferential integritynoyes infonot for MyISAM storage enginenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at shard levelnono
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or rolesnono

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More resources
Microsoft Azure Data ExplorerPlanetScalePrometheusSphinx
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