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DBMS > Microsoft Azure Data Explorer vs. Neo4j vs. RDF4J vs. VictoriaMetrics vs. Virtuoso

System Properties Comparison Microsoft Azure Data Explorer vs. Neo4j vs. RDF4J vs. VictoriaMetrics vs. Virtuoso

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A fast, cost-effective and scalable Time Series DBMS and monitoring solutionVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMS infocolumn orientedGraph DBMSRDF storeTime Series DBMSDocument 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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Score4.26
Rank#78  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#42  Relational DBMS
#2  RDF stores
#9  Search engines
Websiteazure.microsoft.com/­services/­data-explorerneo4j.comrdf4j.orgvictoriametrics.comvirtuoso.openlinksw.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docsrdf4j.org/­documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
docs.openlinksw.com/­virtuoso
DeveloperMicrosoftNeo4j, Inc.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.VictoriaMetricsOpenLink Software
Initial release20192007200420181998
Current releasecloud service with continuous releases5.19, April 2024v1.91, May 20237.2.11, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2.0Open Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaJavaGoC
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
FreeBSD
Linux
macOS
OpenBSD
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalyes infoRDF Schemasyes 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-typesyesyesyes
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.yesnoyes
Secondary indexesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Luceneyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnononoyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
ADO.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 languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Java
PHP
Python
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsyesnoyes infoVirtuoso PL
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handleryesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes using Neo4j Fabricnoneyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlynoneSynchronous replicationChain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoIsolation support depends on the API usednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)noFine-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
Microsoft Azure Data ExplorerNeo4jRDF4J infoformerly known as SesameVictoriaMetricsVirtuoso
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Broad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Largest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
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Recent citations in the news

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog
23 May 2023, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
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Neo4j CTO says new Graph Query Language standard will have 'massive ripple effects'
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GraphDB Goes Open Source
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Green coding - VictoriaMetrics: The efficiency vs complexity trade-off
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How VictoriaMetrics' open source approach led to mass industry adoption
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