DBMS > Cubrid vs. Milvus vs. MonetDB vs. RethinkDB

System Properties Comparison Cubrid vs. Milvus vs. MonetDB vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A DBMS designed for efficient storage of vector data and vector similarity searches

A relational database management system that stores data in columns

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

cubrid.com (korean)
cubrid.org (english)

milvus.io

www.monetdb.org

rethinkdb.com

Technical documentation

cubrid.org/manuals

milvus.io/docs/overview.md

www.monetdb.org/Documentation

rethinkdb.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

MonetDB BV

The Linux Foundation

since July 2017

Initial release

2008

2019

2004

2009

Current release

11.0, January 2021

2.4.4, May 2024

Dec2023 (11.49), December 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C, C++, Java

C++, Go

C++

Server operating systems

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

string, binary, float, bool, date, geometry

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in SQL, C, R

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding via remote tables

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

yes

users and table-level permissions

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus 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

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More resources

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