DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Hive vs. Milvus vs. Trafodion vs. YottaDB

System Properties Comparison Hive vs. Milvus vs. Trafodion vs. YottaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMilvus  Xexclude from comparisonTrafodion  Xexclude from comparisonYottaDB  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesTransactional SQL-on-Hadoop DBMSA fast and solid embedded Key-value store
Primary database modelRelational DBMSVector DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitehive.apache.orgmilvus.iotrafodion.apache.orgyottadb.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homemilvus.io/­docs/­overview.mdtrafodion.apache.org/­documentation.htmlyottadb.com/­resources/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software Foundation, originally developed by HPYottaDB, LLC
Initial release2012201920142001
Current release3.1.3, April 20222.3.4, January 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0
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 languageJavaC++, GoC++, JavaC
Server operating systemsAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
LinuxDocker
Linux
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesno
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 indexesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesby using the Octo plugin
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC++
Java
PHP
Python
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.NetC
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored Procedures
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, via HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and rolesRole based access control and fine grained access rightsfine grained access rights according to SQL-standardUsers and groups based on OS-security mechanisms
More information provided by the system vendor
HiveMilvusTrafodionYottaDB
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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
HiveMilvusTrafodionYottaDB
DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore ...
10 June 2024, AWS Blog

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Altiscale Becomes First Hadoop-as-a-Service to Deliver Apache Hive 0.13
5 June 2024, Yahoo News UK

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

provided by Google News

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

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here