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DBMS > Microsoft Azure Data Explorer vs. Typesense vs. WakandaDB

System Properties Comparison Microsoft Azure Data Explorer vs. Typesense vs. WakandaDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonTypesense  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivityWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMS infocolumn orientedSearch engineObject 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
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score0.80
Rank#209  Overall
#14  Search engines
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteazure.microsoft.com/­services/­data-explorertypesense.orgwakanda.github.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorertypesense.org/­docswakanda.github.io/­doc
DeveloperMicrosoftWakanda SAS
Initial release201920152012
Current releasecloud service with continuous releases2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaScript
Server operating systemshostedLinuxLinux
OS X
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-free infopre-defined schema optionalyes
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.yesno
Secondary indexesall fields are automatically indexedyes
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 infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
JavaScript
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnoyes
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding 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.Multi-source replication using RAFTnone
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 Consistency
Foreign keys infoReferential integritynono
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 persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAzure Active Directory Authenticationyes

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More resources
Microsoft Azure Data ExplorerTypesenseWakandaDB
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