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DBMS > Microsoft Azure Data Explorer vs. Milvus vs. PostgreSQL vs. Weaviate

System Properties Comparison Microsoft Azure Data Explorer vs. Milvus vs. PostgreSQL vs. Weaviate

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonPostgreSQL  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searchesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMS infocolumn orientedVector DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Vector DBMS
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 infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
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
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websiteazure.microsoft.com/­services/­data-explorermilvus.iowww.postgresql.orggithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.mdwww.postgresql.org/­docsweaviate.io/­developers/­weaviate
DeveloperMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerWeaviate B.V.
Initial release201920191989 info1989: Postgres, 1996: PostgreSQL2019
Current releasecloud service with continuous releases2.3.4, January 202416.2, February 20241.19, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infocommercial license available with Weaviate Enterprise
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 MilvusAiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC++, GoCGo
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)yesyes, maps to GraphQL interface
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 infostring, int, float, geo point, date, cross reference, fuzzy references
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.yesnoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesall fields are automatically indexednoyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoyes infostandard with numerous extensionsGraphQL is used as query language
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensionsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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.noyesnoyes
User concepts infoAccess controlAzure Active Directory AuthenticationRole based access control and fine grained access rightsfine grained access rights according to SQL-standardAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Microsoft Azure Data ExplorerMilvusPostgreSQLWeaviate
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
As a database supporting the development of generative AI and semantic search applications...
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
All companies that have data. ​
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
Microsoft Azure Data ExplorerMilvusPostgreSQLWeaviate
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Conferences, events and webinars

Monitoring PostgreSQL with Redgate Monitor
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