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DBMS > Drizzle vs. Hawkular Metrics vs. Milvus vs. Weaviate

System Properties Comparison Drizzle vs. Hawkular Metrics vs. Milvus vs. Weaviate

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonWeaviate  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A 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 modelRelational DBMSTime Series DBMSVector DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.hawkular.orgmilvus.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mdweaviate.io/­developers/­weaviate
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatWeaviate B.V.
Initial release2008201420192019
Current release7.2.4, September 20122.3.4, January 20241.19, May 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
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 languageC++JavaC++, GoGo
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesVector, 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 indexesyesnonoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyes infowith proprietary extensionsnonoGraphQL is used as query language
APIs and other access methodsJDBCHTTP RESTRESTful HTTP APIGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnononono
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.noyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoRole based access control and fine grained access rightsAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
DrizzleHawkular MetricsMilvusWeaviate
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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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. ​
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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...
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DrizzleHawkular MetricsMilvusWeaviate
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