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DBMS > Microsoft Azure Data Explorer vs. Postgres-XL vs. Sphinx

System Properties Comparison Microsoft Azure Data Explorer vs. Postgres-XL vs. Sphinx

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS infocolumn orientedRelational 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
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.71
Rank#83  Overall
#42  Relational DBMS
Score0.56
Rank#218  Overall
#104  Relational DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Websiteazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgsphinxsearch.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationsphinxsearch.com/­docs
DeveloperMicrosoftSphinx Technologies Inc.
Initial release20192014 infosince 2012, originally named StormDB2001
Current releasecloud service with continuous releases10 R1, October 20183.2.1, January 2020
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemshostedLinux
macOS
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.yesyes infoXML type, but no XML query functionality
Secondary indexesall fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionSQL-like query language (SphinxQL)
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ruser defined functionsno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding 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.none
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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoMVCCno
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 Authenticationfine grained access rights according to SQL-standardno
More information provided by the system vendor
Microsoft Azure Data ExplorerPostgres-XLSphinx
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Microsoft Azure Data ExplorerPostgres-XLSphinx
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