DBMS > Altibase vs. Couchbase vs. Cubrid vs. Milvus

System Properties Comparison Altibase vs. Couchbase vs. Cubrid vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Website

altibase.com

www.couchbase.com

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

milvus.io

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.couchbase.com

cubrid.org/manuals

milvus.io/docs/overview.md

Developer

Altibase

Couchbase, Inc.

CUBRID Corporation, CUBRID Foundation

Initial release

1999

2011

2008

2019

Current release

v7.3, 2023, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

11.0, January 2021

2.4.4, May 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2.0

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++

C, C++, Go and Erlang

C, C++, Java

C++, Go

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Windows

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

ANSI SQL-92

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

C
C++
Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

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

Server-side scripts

Stored procedures

stored procedures and stored functions

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Java Stored Procedures

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

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

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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

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...
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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...
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