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DBMS > Hive vs. Milvus vs. Vitess

System Properties Comparison Hive vs. Milvus vs. Vitess

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMilvus  Xexclude from comparisonVitess  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSVector DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitehive.apache.orgmilvus.iovitess.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homemilvus.io/­docs/­overview.mdvitess.io/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookThe Linux Foundation, PlanetScale
Initial release201220192013
Current release3.1.3, April 20222.3.4, January 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses available
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
Docker
Linux
macOS
Data schemeyesyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyes
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.no
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
PHP
Python
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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.yesyes
User concepts infoAccess controlAccess rights for users, groups and rolesRole based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
HiveMilvusVitess
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 scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
HiveMilvusVitess
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Recent citations in the news

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

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How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, ibm.com

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PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

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