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

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonRockset  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA scalable, reliable search and analytics service in the cloud, built on RocksDBTime Series DBMS and big data platform
Primary database modelRelational DBMS infocolumn orientedDocument storeTime 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
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteazure.microsoft.com/­services/­data-explorerrockset.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rockset.comdocs.tdengine.com
DeveloperMicrosoftRocksetTDEngine, previously Taos Data
Initial release201920192019
Current releasecloud service with continuous releases3.0, August 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C
Server operating systemshostedhostedLinux
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesall fields are automatically indexedall fields are automatically indexedno
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetRead-only SQL queries, including JOINsStandard SQL with extensions for time-series applications
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTJDBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
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 serviceAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesyes
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
Eventual 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 persistentyesyesyes
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 AuthenticationAccess rights for users and organizations can be defined via Rockset consoleyes
More information provided by the system vendor
Microsoft Azure Data ExplorerRocksetTDengine
Specific characteristicsTDengineā„¢ 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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