DBMS > Amazon DynamoDB vs. Microsoft Azure Table Storage vs. Milvus vs. OpenQM vs. Realm

System Properties Comparison Amazon DynamoDB vs. Microsoft Azure Table Storage vs. Milvus vs. OpenQM vs. Realm

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A Wide Column Store for rapid development using massive semi-structured datasets

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

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store
Key-value store

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

aws.amazon.com/dynamodb

azure.microsoft.com/en-us/services/storage/tables

milvus.io

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

realm.io

Technical documentation

docs.aws.amazon.com/dynamodb

milvus.io/docs/overview.md

realm.io/docs

Developer

Amazon

Microsoft

Rocket Software, originally Martin Phillips

Realm, acquired by MongoDB in May 2019

Initial release

2012

2019

1993

2014

Current release

2.3.4, January 2024

3.4-12

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

Open Source

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++, Go

Server operating systems

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

with some exceptions

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

APIs and other access methods

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

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

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

by integration with AWS Lambda

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

optimistic locking

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

In-Memory realm

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights based on private key authentication or shared access signatures

Role based access control and fine grained access rights

Access rights can be defined down to the item level

yes

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
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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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