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DBMS > Drizzle vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Virtuoso

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Virtuoso

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  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 fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully 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 DBMSKey-value store
Wide column store
Relational DBMS infocolumn orientedDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
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
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorervirtuoso.openlinksw.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.openlinksw.com/­virtuoso
DeveloperDrizzle project, originally started by Brian AkerGoogleMicrosoftOpenLink Software
Initial release2008201520191998
Current release7.2.4, September 2012cloud service with continuous releases7.2.11, September 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C
Server operating systemsFreeBSD
Linux
OS X
hostedhostedAIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeFixed 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 dateyesnoyes 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.noyesyes
Secondary indexesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoKusto Query Language (KQL), SQL subsetyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
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 languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
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 proceduresnonoYes, possible languages: KQL, Python, Ryes infoVirtuoso PL
Triggersno 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 nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesyes 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 methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure 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
DrizzleGoogle Cloud BigtableMicrosoft Azure Data ExplorerVirtuoso
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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DrizzleGoogle Cloud BigtableMicrosoft Azure Data ExplorerVirtuoso
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