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DBMS > Microsoft Azure Data Explorer vs. Milvus vs. Teradata vs. Virtuoso

System Properties Comparison Microsoft Azure Data Explorer vs. Milvus vs. Teradata vs. Virtuoso

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonTeradata  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searchesA hybrid cloud data analytics software platform (Teradata Vantage)Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMS infocolumn orientedVector DBMSRelational DBMSDocument 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
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score45.33
Rank#21  Overall
#15  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
Websiteazure.microsoft.com/­services/­data-explorermilvus.iowww.teradata.comvirtuoso.openlinksw.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.mddocs.teradata.comdocs.openlinksw.com/­virtuoso
DeveloperMicrosoftTeradataOpenLink Software
Initial release2019201919841998
Current releasecloud service with continuous releases2.3.4, January 2024Teradata Vantage 1.0 MU2, January 20197.2.11, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++, GoC
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
hosted
Linux
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeFixed 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 dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesVector, Numeric and Stringyesyes
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.yesnoyesyes
Secondary indexesall fields are automatically indexednoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoyes infoSQL 2016 + extensionsyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API.NET Client API
HTTP REST
JDBC
JMS Adapter
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
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnoyes infoUDFs, stored procedures, table functions in parallelyes infoVirtuoso PL
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingSharding infoHashingyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.noyesyesyes
User concepts infoAccess controlAzure Active Directory AuthenticationRole based access control and fine grained access rightsfine grained access rights according to SQL-standardFine-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
Microsoft Azure Data ExplorerMilvusTeradataVirtuoso
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Broad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Largest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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More resources
Microsoft Azure Data ExplorerMilvusTeradataVirtuoso
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