DBMS > HarperDB vs. Milvus vs. PouchDB vs. STSdb vs. Transwarp KunDB

System Properties Comparison HarperDB vs. Milvus vs. PouchDB vs. STSdb vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

JavaScript DBMS with an API inspired by CouchDB

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

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

Score	0.55
Rank	#252	Overall
	#38	Document stores

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	0.14
Rank	#340	Overall
	#148	Relational DBMS

Website

www.harperdb.io

milvus.io

pouchdb.com

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/kundb

Technical documentation

docs.harperdb.io/docs

milvus.io/docs/overview.md

pouchdb.com/guides

Developer

HarperDB

Apache Software Foundation

STS Soft SC

Transwarp

Initial release

2017

2019

2012

2011

Current release

3.1, August 2021

2.3.4, January 2024

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

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

Node.js

C++, Go

JavaScript

Server operating systems

Linux
OS X

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

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

Windows

Data scheme

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

Vector, Numeric and String

yes

primitive types and user defined types (classes)

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

via views

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

JavaScript

C#
Java

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

Sharding

with a proxy-based framework, named couchdb-lounge

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

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

Access rights for users and roles

Role based access control and fine grained access rights

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

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