DBMS > Microsoft Azure SQL Database vs. Milvus vs. Tkrzw vs. VoltDB

System Properties Comparison Microsoft Azure SQL Database vs. Milvus vs. Tkrzw vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering with high compatibility to Microsoft SQL Server

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

azure.microsoft.com/en-us/products/azure-sql/database

milvus.io

dbmx.net/tkrzw

www.voltdb.com

Technical documentation

docs.microsoft.com/en-us/azure/azure-sql

milvus.io/docs/overview.md

docs.voltdb.com

Developer

Microsoft

Mikio Hirabayashi

VoltDB Inc.

Initial release

2010

2019

2020

2010

Current release

V12

2.3.4, January 2024

0.9.3, August 2020

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Linux
OS X

for development

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C++
Java
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

none

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Users and roles with access to stored procedures

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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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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7 February 2017, Matthias Gelbmann

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Vector databases
2 June 2023, Matthias Gelbmann

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provided by Google News

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