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DBMS > AnzoGraph DB vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. PostgreSQL

System Properties Comparison AnzoGraph DB vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. PostgreSQL

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationNatively in-memory DBMS with options for persistency, high-availability and clusteringFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
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 Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score0.73
Rank#227  Overall
#104  Relational DBMS
#18  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score645.05
Rank#4  Overall
#4  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.mcobject.comazure.microsoft.com/­services/­data-explorerwww.postgresql.org
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docs
DeveloperCambridge SemanticsMcObjectMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2018200120191989 info1989: Postgres, 1996: PostgreSQL
Current release2.3, January 20218.2, 2021cloud service with continuous releases16.2, February 2024
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC and C++C
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes 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.nono infosupport of XML interfaces availableyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infowith the option: eXtremeSQLKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensions
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Java
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyes infoby defining eventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning / shardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.yesyesnono
User concepts infoAccess controlAccess rights for users and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
AnzoGraph DBeXtremeDBMicrosoft Azure Data ExplorerPostgreSQL
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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More resources
AnzoGraph DBeXtremeDBMicrosoft Azure Data ExplorerPostgreSQL
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