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DBMS > Elasticsearch vs. Milvus vs. Weaviate

System Properties Comparison Elasticsearch vs. Milvus vs. Weaviate

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonMilvus  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 metricA DBMS designed for efficient storage of vector data and vector similarity searchesAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelSearch engine
Vector DBMS
Vector DBMSVector DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score132.32
Rank#8  Overall
#1  Search engines
#1  Vector DBMS
Score2.82
Rank#95  Overall
#5  Vector DBMS
Score1.70
Rank#135  Overall
#9  Vector DBMS
Websitewww.elastic.co/­elasticsearchmilvus.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlmilvus.io/­docs/­overview.mdweaviate.io/­developers/­weaviate
DeveloperElasticWeaviate B.V.
Initial release201020192019
Current release8.6, January 20232.4.4, May 20241.19, May 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2.0Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonono
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++, GoGo
Server operating systemsAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyes 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.nonono
Secondary indexesyes infoAll search 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 languagenoGraphQL is used as query language
APIs and other access methodsJava API
RESTful HTTP/JSON API
RESTful HTTP APIGraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesnono
Triggersyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornono
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, allBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyesyes
User concepts infoAccess controlRole based access control and fine grained access rightsAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
ElasticsearchMilvusWeaviate
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
ElasticsearchMilvusWeaviate
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