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DBMS > Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. WakandaDB

System Properties Comparison Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. WakandaDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMS infocolumn orientedWide column storeObject 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)
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.34
Rank#60  Overall
#34  Relational DBMS
Score5.67
Rank#75  Overall
#5  Wide column stores
Score0.02
Rank#349  Overall
#19  Object oriented DBMS
Websiteazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tableswakanda.github.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdoc.wakanda.org/­home2.en.html#/­Datastore/­Introduction.200-588937.en.html
DeveloperMicrosoftMicrosoftWakanda SAS
Initial release201920122012
Current releasecloud service with continuous releases2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPLv3, extended commercial license 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++, JavaScript
Server operating systemshostedhostedLinux
OS X
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-typesyesyes
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 indexedno
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIRESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnoyes
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID
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.nonono
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesyes
More information provided by the system vendor
Microsoft Azure Data ExplorerMicrosoft Azure Table StorageWakandaDB
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
Licensing and pricing modelsAn Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more

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Microsoft Azure Data ExplorerMicrosoft Azure Table StorageWakandaDB
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