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DBMS > Citus vs. EXASOL vs. Microsoft Azure Data Explorer vs. Netezza vs. Virtuoso

System Properties Comparison Citus vs. EXASOL vs. Microsoft Azure Data Explorer vs. Netezza vs. Virtuoso

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEXASOL  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Fully managed big data interactive analytics platformData warehouse and analytics appliance part of IBM PureSystemsVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
Secondary database modelsDocument storeDocument 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
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational 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
Websitewww.citusdata.comwww.exasol.comazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezzavirtuoso.openlinksw.com
Technical documentationdocs.citusdata.comwww.exasol.com/­resourcesdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.openlinksw.com/­virtuoso
DeveloperExasolMicrosoftIBMOpenLink Software
Initial release20102000201920001998
Current release8.1, December 2018cloud service with continuous releases7.2.11, September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialcommercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC
Server operating systemsLinuxhostedLinux infoincluded in applianceAIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes 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 dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.yes infospecific XML type available, but no XML query functionalitynoyesyes
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesKusto Query Language (KQL), SQL subsetyesyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.Net
JDBC
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
OLE DB
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
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsYes, possible languages: KQL, Python, Ryesyes infoVirtuoso PL
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationChain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
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.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAzure Active Directory AuthenticationUsers with fine-grained authorization conceptFine-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
CitusEXASOLMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBMVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale โ€” as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for โ€” Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including โ€” European Union (EU) US Government...
» more
Market metricsLargest installed-base โ€‹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
CitusEXASOLMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBMVirtuoso
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