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

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesTime Series DBMS and big data platform
Primary database modelRelational DBMS infocolumn orientedSearch engineTime Series 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)
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteazure.microsoft.com/­services/­data-explorersphinxsearch.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docsdocs.tdengine.com
DeveloperMicrosoftSphinx Technologies Inc.TDEngine, previously Taos Data
Initial release201920012019
Current releasecloud service with continuous releases3.5.1, February 20233.0, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL V3, also commercial editions 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 languageC++C
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
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-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 fieldsno
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)Standard SQL with extensions for time-series applications
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
RESTful HTTP API
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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, via alarm monitoring
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.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
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.no
User concepts infoAccess controlAzure Active Directory Authenticationnoyes
More information provided by the system vendor
Microsoft Azure Data ExplorerSphinxTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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