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DBMS > Microsoft Azure Data Explorer vs. QuestDB vs. Sphinx

System Properties Comparison Microsoft Azure Data Explorer vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA high performance, low latency Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS infocolumn orientedTime 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)
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.71
Rank#83  Overall
#42  Relational DBMS
Score0.28
Rank#266  Overall
#20  Time Series DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Websiteazure.microsoft.com/­services/­data-explorerquestdb.iosphinxsearch.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperMicrosoftQuestDB LimitedSphinx Technologies Inc.
Initial release201920142001
Current releasecloud service with continuous releases3.2.1, January 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)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-typesyesno
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 indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTProprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)Sharding 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.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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.nono
User concepts infoAccess controlAzure Active Directory Authenticationno
More information provided by the system vendor
Microsoft Azure Data ExplorerQuestDBSphinx
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more

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Microsoft Azure Data ExplorerQuestDBSphinx
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