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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 searchesA cloud-native, realtime vector search engine integrating scalable machine learning models
Primary database modelSearch engineSearch engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score155.08
Rank#8  Overall
#1  Search engines
Score0.37
Rank#264  Overall
#18  Search engines
Score0.12
Rank#308  Overall
#19  Search engines
Websitewww.elastic.co/­elasticsearchmilvus.iogithub.com/­semi-technologies/­weaviate
weaviate.io
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlmilvus.io/­docs/­overview.mdweaviate.io/­developers/­weaviate/­current
DeveloperElasticSeMI Technologies B.V.
Initial release201020192017
Current release7.8.0, June 20202.0, January 20221.0.3, January 2021
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.
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 dateyesNumeric 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
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 integrationnono
User concepts infoAccess controlnoOpenID 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
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosVideo media : video understanding, video deduplication. E-commerce and mobile applications...
» more
As a stand-alone vector search engine, or use one of the many modules (transformers,...
» more
Key customersMilvus is trusted by over 1,000 enterprises, including Baidu, eBay, IKEA, LINE, Shopee,...
» more
A ll companies that have data. ​
» more
Market metricsAs of March 2022, 9.8k+ GitHub stars 1.4k+ Github forks 871k+ docker pulls 2k+ community...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Managed...
» more
Weaviate is open-source, and free to use. We also offer Fully managed Weaviate on...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
ElasticsearchMilvusWeaviate
DB-Engines blog posts

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Recent citations in the news

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What Is Vector Similarity Search? | Business Applications of Vector Search
11 August 2021, CIO Insight

Milvus, the AI Search Engine, Originally Developed by Zilliz Joins LF AI as New Incubation Project
10 April 2020, PR Newswire

The Recommendation System
15 February 2022, News | Europeana Pro

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Amsterdam-based startup SeMI Technologies raises €14.1M for its open-source vector search engine Weaviate
23 February 2022, Silicon Canals

SeMI Technologies’ search engine opens up new ways to query your data
22 February 2022, TechCrunch

Getting Started with the Weaviate Vector Search Engine
18 May 2020, hackernoon.com

Database technology evolves to combine machine learning and data storage
7 March 2022, VentureBeat

Weaviate Is A Search Engine For Vector Embeddings
11 May 2020, hackernoon.com

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