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DBMS > Hypertable vs. Microsoft Azure Data Explorer vs. RDFox

System Properties Comparison Hypertable vs. Microsoft Azure Data Explorer vs. RDFox

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDFox  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platformHigh performance knowledge graph and semantic reasoning engine
Primary database modelWide column storeRelational DBMS infocolumn orientedGraph DBMS
RDF 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)
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Websiteazure.microsoft.com/­services/­data-explorerwww.oxfordsemantic.tech
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oxfordsemantic.tech
DeveloperHypertable Inc.MicrosoftOxford Semantic Technologies
Initial release200920192017
Current release0.9.8.11, March 2016cloud service with continuous releases6.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
macOS
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yes infoRDF schemas
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.yes
Secondary indexesrestricted infoonly exact value or prefix value scansall fields are automatically indexed
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsC++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
Java
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, R
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.replication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
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.noyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationRoles, resources, and access types

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More resources
HypertableMicrosoft Azure Data ExplorerRDFox
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