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DBMS > Amazon Aurora vs. Drizzle vs. Hive vs. Microsoft Azure Data Explorer vs. Virtuoso

System Properties Comparison Amazon Aurora vs. Drizzle vs. Hive vs. Microsoft Azure Data Explorer vs. Virtuoso

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDrizzle  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVirtuoso  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.data warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS infocolumn orientedDocument 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
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  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
Websiteaws.amazon.com/­rds/­aurorahive.apache.orgazure.microsoft.com/­services/­data-explorervirtuoso.openlinksw.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.openlinksw.com/­virtuoso
DeveloperAmazonDrizzle project, originally started by Brian AkerApache Software Foundation infoinitially developed by FacebookMicrosoftOpenLink Software
Initial release20152008201220191998
Current release7.2.4, September 20123.1.3, April 2022cloud service with continuous releases7.2.11, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2commercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC
Server operating systemshostedFreeBSD
Linux
OS X
All OS with a Java VMhostedAIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)yes 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 dateyesyesyesyes 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.yesyesyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsADO.NET
JDBC
ODBC
JDBCJDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
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 languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Java
PHP
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresyesnoyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Ryes infoVirtuoso PL
Triggersyesno infohooks for callbacks inside the server can be used.noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
selectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and rolesAzure Active Directory AuthenticationFine-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
Amazon AuroraDrizzleHiveMicrosoft Azure Data ExplorerVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsLargest installed-base ​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
Amazon AuroraDrizzleHiveMicrosoft Azure Data ExplorerVirtuoso
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