DBMS > GeoMesa vs. Milvus vs. Newts vs. PouchDB vs. STSdb

System Properties Comparison GeoMesa vs. Milvus vs. Newts vs. PouchDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Time Series DBMS based on Cassandra

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

Primary database model

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.geomesa.org

milvus.io

opennms.github.io/newts

pouchdb.com

github.com/STSSoft/STSdb4

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

milvus.io/docs/overview.md

github.com/OpenNMS/newts/wiki

pouchdb.com/guides

Developer

CCRi and others

OpenNMS Group

Apache Software Foundation

STS Soft SC

Initial release

2014

2019

2014

2012

2011

Current release

4.0.5, February 2024

2.3.4, January 2024

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

Scala

C++, Go

Java

JavaScript

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

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

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

HTTP REST
Java API

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

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

Java

JavaScript

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor

based on Cassandra

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

depending on storage layer

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Role based access control and fine grained access rights

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

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Vector databases
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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