DBMS > ArangoDB vs. Cubrid vs. Linter vs. Milvus

System Properties Comparison ArangoDB vs. Cubrid vs. Linter vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

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

RDBMS for high security requirements

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

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	3.77
Rank	#87	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores
	#10	Search engines

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Website

arangodb.com

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

linter.ru

milvus.io

Technical documentation

docs.arangodb.com

cubrid.org/manuals

milvus.io/docs/overview.md

Social network pages

Developer

ArangoDB Inc.

CUBRID Corporation, CUBRID Foundation

relex.ru

Initial release

2012

2008

1990

2019

Current release

3.11.5, November 2023

11.0, January 2021

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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.

ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++

C, C++, Java

C and C++

C++, Go

Server operating systems

Linux
OS X
Windows

Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

automatically recognizes schema within a collection

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes

Vector, Numeric and String

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

APIs and other access methods

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

Server-side scripts

Stored procedures

JavaScript

Java Stored Procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

yes

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

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

Competitive advantages

Consolidation: As a native multi-model database, can be used as a full blown document...
» more

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

Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
» more

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

Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more

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

Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more

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

Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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

DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

ArangoDB Announces Release of ArangoDB 3.11 for Search, Graph and Analytics - High-Performance Computing ...
30 May 2023, insideHPC

How to Build Knowledge Graph Enhanced Chatbot with ChatGPT and ArangoDB
30 June 2023, DataDrivenInvestor

ArangoDB brings yet more money into graph database market with $27.8M round
6 October 2021, SiliconANGLE News

ArangoDB expands scope of graph database platform
6 October 2022, TechTarget

Graph, machine learning, hype, and beyond: ArangoDB open source multi-model database releases version 3.7
27 August 2020, ZDNet

provided by Google News

What Is Milvus Vector Database?
6 October 2023, The New Stack

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

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 Cloud boosts vector database performance
31 January 2024, InfoWorld

provided by Google News

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