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DBMS > Ehcache vs. gStore vs. Microsoft Azure Data Explorer vs. RDFox

System Properties Comparison Ehcache vs. gStore vs. Microsoft Azure Data Explorer vs. RDFox

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisongStore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA native Graph DBMS to store and maintain very large RDF datasets.Fully managed big data interactive analytics platformHigh performance knowledge graph and semantic reasoning engine
Primary database modelKey-value storeGraph DBMS
RDF store
Relational 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
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.04
Rank#359  Overall
#37  Graph DBMS
#18  RDF stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Websitewww.ehcache.orgen.gstore.cnazure.microsoft.com/­services/­data-explorerwww.oxfordsemantic.tech
Technical documentationwww.ehcache.org/­documentationen.gstore.cn/­#/­enDocsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oxfordsemantic.tech
DeveloperTerracotta Inc, owned by Software AGMicrosoftOxford Semantic Technologies
Initial release2009201620192017
Current release3.10.0, March 20221.2, November 2023cloud service with continuous releases6.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoBSDcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsAll OS with a Java VMLinuxhostedLinux
macOS
Windows
Data schemeschema-freeschema-free and OWL/RDFS-schema supportFixed schema with schema-less datatypes (dynamic)yes infoRDF schemas
Typing infopredefined data types such as float or dateyesyesyes 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.nonoyes
Secondary indexesnoall fields are automatically indexed
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJCacheHTTP API
SPARQL 1.1
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
Java
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, R
Triggersyes infoCache Event Listenersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryes 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 methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual 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 datayes infosupports JTA and can work as an XA resourceyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnoUsers, roles and permissions, Role-Based Access Control (RBAC) supportedAzure Active Directory AuthenticationRoles, resources, and access types

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More resources
EhcachegStoreMicrosoft Azure Data ExplorerRDFox
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