DBMS > KairosDB vs. LevelDB vs. Milvus vs. PouchDB vs. SQLite

System Properties Comparison KairosDB vs. LevelDB vs. Milvus vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/kairosdb/kairosdb

github.com/google/leveldb

milvus.io

pouchdb.com

www.sqlite.org

Technical documentation

kairosdb.github.io

github.com/google/leveldb/blob/main/doc/index.md

milvus.io/docs/overview.md

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

Google

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2013

2011

2019

2012

2000

Current release

1.2.2, November 2018

1.23, February 2021

2.3.4, January 2024

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

Public Domain

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

Java

C++

C++, Go

JavaScript

Server operating systems

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

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

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

with automatic compression on writes

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

simple password-based access control

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...
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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...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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