DBMS > Elasticsearch vs. Milvus vs. Qdrant
System Properties Comparison Elasticsearch vs. Milvus vs. Qdrant
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|Editorial information provided by DB-Engines|
|Name||Elasticsearch Xexclude from comparison||Milvus Xexclude from comparison||Qdrant Xexclude from comparison|
|Description||A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric||A DBMS designed for efficient storage of vector data and vector similarity searches||A high-performance vector database with neural network or semantic-based matching|
|Primary database model||Search engine||Vector DBMS||Vector DBMS|
|Secondary database models||Document store|
|Current release||8.6, January 2023||2.2, November 2022|
|License Commercial or Open Source||Open Source Elastic License||Open Source Apache Version 2.0||Open Source Apache Version 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Zilliz Cloud – Cloud-native service for Milvus|
|Implementation language||Java||C++, Go||Rust|
|Server operating systems||All OS with a Java VM||Linux|
macOS 10.14 or later
Windows with WSL 2 enabled
|Data scheme||schema-free Flexible type definitions. Once a type is defined, it is persistent||schema-free|
|Typing predefined data types such as float or date||yes||Vector, Numeric and String||Numbers, Strings, Geo, Boolean|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||no||no|
|Secondary indexes||yes All search fields are automatically indexed||no||yes Keywords, numberic ranges, geo, full-text|
|SQL Support of SQL||SQL-like query language||no||no|
|APIs and other access methods||Java API|
RESTful HTTP/JSON API
|RESTful HTTP API||gRPC|
RESTful HTTP/JSON API OpenAPI 3.0
|Supported programming languages||.Net|
Community Contributed Clients
|Server-side scripts Stored procedures||yes||no|
|Triggers||yes by using the 'percolation' feature||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||yes||Collection-level replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||ES-Hadoop Connector||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all||Bounded Staleness|
|Eventual Consistency, tunable consistency|
|Foreign keys Referential integrity||no||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||Memcached and Redis integration||no||yes|
|User concepts Access control||no||Key-based authentication|
|More information provided by the system vendor|
|Specific characteristics||Milvus is an open-source and cloud-native vector database built for production-ready...|
|Competitive advantages||Highly available, versatile, and robust with millisecond latency. Supports batch...|
|Typical application scenarios||Video media : video understanding, video deduplication. E-commerce and mobile applications...|
|Key customers||Milvus is trusted by over 1,000 enterprises, including Baidu, eBay, IKEA, LINE, Shopee,...|
|Market metrics||As of February 2023, 14k+ GitHub stars 2M+ downloads and installations 1000+ enterprise...|
|Licensing and pricing models||Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...|
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SRE (Data Dog)
Senior Software Engineer, High Performance Computing
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