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

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMS infocolumn orientedSearch engineGraph DBMS
Object oriented 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)
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.71
Rank#83  Overall
#42  Relational DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Score0.11
Rank#299  Overall
#28  Graph DBMS
#16  Object oriented DBMS
Websiteazure.microsoft.com/­services/­data-explorersphinxsearch.comvelocitydb.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docsvelocitydb.com/­UserGuide
DeveloperMicrosoftSphinx Technologies Inc.VelocityDB Inc
Initial release201920012011
Current releasecloud service with continuous releases3.2.1, January 20207.x
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availablecommercial
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 languageC++C#
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Any that supports .NET
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-typesnoyes
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 indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)no
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol.Net
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAzure Active Directory AuthenticationnoBased on Windows Authentication
More information provided by the system vendor
Microsoft Azure Data ExplorerSphinxVelocityDB
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 ExplorerSphinxVelocityDB
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