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DBMS > Fauna vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Virtuoso

System Properties Comparison Fauna vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Virtuoso

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Editorial information provided by DB-Engines
NameFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Fully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedWide column storeDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score4.27
Rank#73  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#39  Relational DBMS
#2  RDF stores
#9  Search engines
Websitefauna.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tablesvirtuoso.openlinksw.com
Technical documentationdocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.openlinksw.com/­virtuoso
DeveloperFauna, Inc.MicrosoftMicrosoftOpenLink Software
Initial release2014201920121998
Current releasecloud service with continuous releases7.2.11, September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC
Server operating systemshostedhostedhostedAIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes infoSQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type
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-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.noyesnoyes
Secondary indexesyesall fields are automatically indexednoyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT
Supported programming languagesC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, Rnoyes infoVirtuoso PL
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes 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.Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlIdentity management, authentication, and access controlAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesFine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Fauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsLargest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsAvailable in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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Fauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageVirtuoso
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