DBMS > Microsoft Azure Synapse Analytics vs. Milvus vs. mSQL vs. Sadas Engine vs. Spark SQL

System Properties Comparison Microsoft Azure Synapse Analytics vs. Milvus vs. mSQL vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

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

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

azure.microsoft.com/services/synapse-analytics

milvus.io

hughestech.com.au/products/msql

www.sadasengine.com

spark.apache.org/sql

Technical documentation

docs.microsoft.com/azure/synapse-analytics

milvus.io/docs/overview.md

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Microsoft

Hughes Technologies

SADAS s.r.l.

Apache Software Foundation

Initial release

2016

2019

1994

2006

2014

Current release

2.4.4, May 2024

4.4, October 2021

8.0

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free licenses can be provided

commercial

free trial version available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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

C++

Scala

Server operating systems

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

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

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

yes

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

yes

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Supported programming languages

C#
Java
PHP

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

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C#
C++
Groovy
Java
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

managed by 'Learn by Usage'

User concepts

Access control

yes

Role based access control and fine grained access rights

Access rights for users, groups and roles according to SQL-standard

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

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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