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DBMS > Microsoft Azure Data Explorer vs. Riak KV vs. SWC-DB

System Properties Comparison Microsoft Azure Data Explorer vs. Riak KV vs. SWC-DB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeA high performance, scalable Wide Column DBMS
Primary database modelRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesWide column store
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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.62
Rank#62  Overall
#34  Relational DBMS
Score6.72
Rank#59  Overall
#7  Key-value stores
Score0.00
Rank#353  Overall
#13  Wide column stores
Websiteazure.microsoft.com/­services/­data-explorerriak.com/­products/­riak-kvgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperMicrosoftBasho TechnologiesAlex Kashirin
Initial release201920092020
Current releasecloud service with continuous releases2.1.0, April 20150.5, April 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++
Server operating systemshostedLinux
OS X
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
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-typesno
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.yesnono
Secondary indexesall fields are automatically indexedrestricted
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoSQL-like query language
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Proprietary protocol
Thrift
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RJavaScript and Erlangno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be stored
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.nono
User concepts infoAccess controlAzure Active Directory Authenticationno
More information provided by the system vendor
Microsoft Azure Data ExplorerRiak KVSWC-DB infoSuper Wide Column Database
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, B├╝hler, 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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More resources
Microsoft Azure Data ExplorerRiak KVSWC-DB infoSuper Wide Column Database
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