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DBMS > Atos Standard Common Repository vs. BaseX vs. EXASOL vs. GraphDB vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. BaseX vs. EXASOL vs. GraphDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBaseX  Xexclude from comparisonEXASOL  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.Fully managed big data interactive analytics platform
Primary database modelDocument store
Key-value store
Native XML DBMSRelational DBMSGraph DBMS
RDF store
Relational DBMS infocolumn oriented
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score3.32
Rank#91  Overall
#6  Graph DBMS
#4  RDF stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorybasex.orgwww.exasol.comwww.ontotext.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.basex.orgwww.exasol.com/­resourcesgraphdb.ontotext.com/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorer
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperAtos Convergence CreatorsBaseX GmbHExasolOntotextMicrosoft
Initial release20162007200020002019
Current release170310.7, August 202310.4, October 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsLinuxLinux
OS X
Windows
All OS with a Java VM
Linux
OS X
Windows
hosted
Data schemeSchema and schema-less with LDAP viewsschema-freeyesschema-free and OWL/RDFS-schema support; RDF shapesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalno infoXQuery supports typesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesnonoyes
Secondary indexesyesyesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesall fields are automatically indexed
SQL infoSupport of SQLnonoyesstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCKusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
.Net
JDBC
ODBC
WebSocket
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
Java
Lua
Python
R
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesuser defined functionswell-defined plugin interfaces; JavaScript server-side extensibilityYes, possible languages: KQL, Python, R
Triggersyesyes infovia eventsyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes infoConstraint checkingno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsmultiple readers, single writerACIDACIDno
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.yesyesno
User concepts infoAccess controlLDAP bind authenticationUsers with fine-grained authorization concept on 4 levelsAccess rights for users, groups and roles according to SQL-standardDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.Azure Active Directory Authentication
More information provided by the system vendor
Atos Standard Common RepositoryBaseXEXASOLGraphDB infoformer name: OWLIMMicrosoft Azure Data Explorer
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
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