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DBMS > Microsoft Azure Data Explorer vs. NSDb vs. RDF4J vs. WakandaDB

System Properties Comparison Microsoft Azure Data Explorer vs. NSDb vs. RDF4J vs. WakandaDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMS infocolumn orientedTime Series DBMSRDF 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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Websiteazure.microsoft.com/­services/­data-explorernsdb.iordf4j.orgwakanda.github.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecturerdf4j.org/­documentationwakanda.github.io/­doc
DeveloperMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Wakanda SAS
Initial release2019201720042012
Current releasecloud service with continuous releases2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ScalaJavaC++, JavaScript
Server operating systemshostedLinux
macOS
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasyes
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-typesyes: int, bigint, decimal, stringyesyes
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 indexedall fields are automatically indexedyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query languagenono
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
Java
PHP
Python
JavaScript
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnoyesyes
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes infoin-memory storage is supported as wellyes
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 Authenticationnoyes

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More resources
Microsoft Azure Data ExplorerNSDbRDF4J infoformerly known as SesameWakandaDB
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