DBMS > Milvus vs. OrigoDB vs. PouchDB vs. RethinkDB vs. Transwarp KunDB

System Properties Comparison Milvus vs. OrigoDB vs. PouchDB vs. RethinkDB vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

JavaScript DBMS with an API inspired by CouchDB

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Vector DBMS

Document store
Object oriented DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

www.transwarp.cn/en/product/kundb

Technical documentation

milvus.io/docs/overview.md

origodb.com/docs

pouchdb.com/guides

rethinkdb.com/docs

Developer

Robert Friberg et al

Apache Software Foundation

The Linux Foundation

since July 2017

Transwarp

Initial release

2019

2009

under the name LiveDB

2012

2009

Current release

2.3.4, January 2024

7.1.1, June 2019

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

commercial

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++, Go

JavaScript

C++

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

Vector, Numeric and String

User defined using .NET types and collections

yes

string, binary, float, bool, date, geometry

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.

can be achieved using .NET

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

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

.Net

JavaScript

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

Triggers

yes

Domain Events

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

range based

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Role based access control and fine grained access rights

Role based authorization

yes

users and table-level permissions

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

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.

Related products and services

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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4 August 2014, Paul Andlinger

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Recent citations in the news

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

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Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

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How to Use RethinkDB with Node.js Applications — SitePoint
16 December 2015, SitePoint

An introduction to building realtime apps with RethinkDB
9 July 2022, devm.io

Stripe acquires team behind NoSQL database startup RethinkDB
5 October 2016, VentureBeat

RethinkDB is dead, and MongoDB isn't what killed it
24 January 2017, TechRepublic

How to deploy RethinkDB using Docker
14 February 2018, Packt Hub

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