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DBMS > AnzoGraph DB vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Virtuoso

System Properties Comparison AnzoGraph DB vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Virtuoso

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonSphinx  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationFully managed big data interactive analytics platformWidely used RDBMSOpen source search engine for searching in data from different sources, e.g. relational databasesVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelGraph DBMS
RDF store
Relational DBMS infocolumn orientedRelational DBMSSearch engineDocument 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
Document store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score4.27
Rank#73  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#39  Relational DBMS
#2  RDF stores
#9  Search engines
Websitecambridgesemantics.com/­anzographazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databasesphinxsearch.comvirtuoso.openlinksw.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasesphinxsearch.com/­docsdocs.openlinksw.com/­virtuoso
DeveloperCambridge SemanticsMicrosoftOracleSphinx Technologies Inc.OpenLink Software
Initial release20182019198020011998
Current release2.3, January 2021cloud service with continuous releases23c, September 20233.5.1, February 20237.2.11, September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++C
Server operating systemsLinuxhostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeSchema-free and OWL/RDFS-schema supportFixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsyesyes 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 dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnoyes
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.noyesyesyes
Secondary indexesnoall fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.Kusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsSQL-like query language (SphinxQL)yes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary protocolADO.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++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functions and aggregatesYes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possiblenoyes infoVirtuoso PL
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
noneChain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQLnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoisolation level can be parameterizednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'yes
User concepts infoAccess controlAccess rights for users and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standardnoFine-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
AnzoGraph DBMicrosoft Azure Data ExplorerOracleSphinxVirtuoso
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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More resources
AnzoGraph DBMicrosoft Azure Data ExplorerOracleSphinxVirtuoso
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