DBMS > 4D vs. Microsoft SQL Server vs. Milvus vs. OpenQM

System Properties Comparison 4D vs. Microsoft SQL Server vs. Milvus vs. OpenQM

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Microsofts flagship relational DBMS

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

Vector DBMS

Multivalue DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

www.4d.com

www.microsoft.com/en-us/sql-server

milvus.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

developer.4d.com

learn.microsoft.com/en-US/sql/sql-server

milvus.io/docs/overview.md

Developer

4D, Inc

Microsoft

Rocket Software, originally Martin Phillips

Initial release

1984

1989

2019

1993

Current release

v20, April 2023

SQL Server 2022, November 2022

2.3.4, January 2024

3.4-12

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

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++, Go

Server operating systems

OS X
Windows

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

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

Immediate 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

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Access rights can be defined down to the item level

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.