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DBMS > Elasticsearch vs. Microsoft Azure Data Explorer vs. Milvus vs. SurrealDB vs. Weaviate

System Properties Comparison Elasticsearch vs. Microsoft Azure Data Explorer vs. Milvus vs. SurrealDB vs. Weaviate

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonSurrealDB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searchesA fully ACID transactional, developer-friendly, multi-model DBMSAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelSearch engineRelational DBMS infocolumn orientedVector DBMSDocument store
Graph DBMS
Vector DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.elastic.co/­elasticsearchazure.microsoft.com/­services/­data-explorermilvus.iosurrealdb.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.mdsurrealdb.com/­docsweaviate.io/­developers/­weaviate
DeveloperElasticMicrosoftSurrealDB LtdWeaviate B.V.
Initial release20102019201920222019
Current release8.6, January 2023cloud service with continuous releases2.3.4, January 2024v1.1.1, January 20241.19, May 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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 languageJavaC++, GoRustGo
Server operating systemsAll OS with a Java VMhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentFixed schema with schema-less datatypes (dynamic)schema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyes 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.noyesnono
Secondary indexesyes infoAll search fields are automatically indexedall fields are automatically indexednoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetnoSQL-like query languageGraphQL is used as query language
APIs and other access methodsJava API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIGraphQL
RESTful HTTP API
WebSocket
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnono
Triggersyes infoby using the 'percolation' featureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
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.Memcached and Redis integrationnoyesyes
User concepts infoAccess controlAzure Active Directory AuthenticationRole based access control and fine grained access rightsyes, based on authentication and database rulesAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
ElasticsearchMicrosoft Azure Data ExplorerMilvusSurrealDBWeaviate
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...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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As a database supporting the development of generative AI and semantic search applications...
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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All companies that have data. ​
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
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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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ElasticsearchMicrosoft Azure Data ExplorerMilvusSurrealDBWeaviate
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