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DBMS > Microsoft Azure Data Explorer vs. Neo4j vs. Postgres-XL vs. PostgreSQL vs. Stardog

System Properties Comparison Microsoft Azure Data Explorer vs. Neo4j vs. Postgres-XL vs. PostgreSQL vs. Stardog

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPostgreSQL  Xexclude from comparisonStardog  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 offeringsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMS infocolumn orientedGraph DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Graph 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
Document store
Spatial DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
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
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteazure.microsoft.com/­services/­data-explorerneo4j.comwww.postgres-xl.orgwww.postgresql.orgwww.stardog.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docswww.postgres-xl.org/­documentationwww.postgresql.org/­docsdocs.stardog.com
DeveloperMicrosoftNeo4j, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerStardog-Union
Initial release201920072014 infosince 2012, originally named StormDB1989 info1989: Postgres, 1996: PostgreSQL2010
Current releasecloud service with continuous releases5.19, April 202410 R1, October 201816.3, May 20247.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoMozilla public licenseOpen Source infoBSDcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ScalaCCJava
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
macOS
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalyesyesschema-free and OWL/RDFS-schema support
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-typesyesyesyesyes
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.yesyes infoXML type, but no XML query functionalityyes infospecific XML-type available, but no XML query functionality.no infoImport/export of XML data possible
Secondary indexesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Luceneyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoyes infodistributed, parallel query executionyes infostandard with numerous extensionsYes, compatible with all major SQL variants through dedicated BI/SQL Server
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
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
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
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handleryesyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes using Neo4j Fabrichorizontal partitioningpartitioning by range, list and (since PostgreSQL 11) by hashnone
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 onlySource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknononono
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
Immediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoMVCCACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles
More information provided by the system vendor
Microsoft Azure Data ExplorerNeo4jPostgres-XLPostgreSQLStardog
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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