DBMS > Cubrid vs. Milvus vs. mSQL vs. SpaceTime vs. SwayDB

System Properties Comparison Cubrid vs. Milvus vs. mSQL vs. SpaceTime vs. SwayDB

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Relational 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
	#3	Vector DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

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

milvus.io

hughestech.com.au/products/msql

www.mireo.com/spacetime

swaydb.simer.au

Technical documentation

cubrid.org/manuals

milvus.io/docs/overview.md

Developer

CUBRID Corporation, CUBRID Foundation

Hughes Technologies

Mireo

Simer Plaha

Initial release

2008

2019

1994

2020

2018

Current release

11.0, January 2021

2.3.4, January 2024

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

free licenses can be provided

commercial

Open Source

GNU Affero GPL V3.0

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++, Java

C++, Go

C++

Scala

Server operating systems

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

A subset of ANSI SQL is implemented

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

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

C
C++
Delphi
Java
Perl
PHP
Tcl

C#
C++
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

yes

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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