DBMS > LevelDB vs. Microsoft Azure Cosmos DB vs. PouchDB vs. Tkrzw

System Properties Comparison LevelDB vs. Microsoft Azure Cosmos DB vs. PouchDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

JavaScript DBMS with an API inspired by CouchDB

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Key-value store

Secondary database models

Spatial DBMS

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

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	0.09
Rank	#354	Overall
	#51	Key-value stores

Website

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

pouchdb.com

dbmx.net/tkrzw

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

pouchdb.com/guides

Developer

Google

Microsoft

Apache Software Foundation

Mikio Hirabayashi

Initial release

2011

2014

2012

2020

Current release

1.23, February 2021

7.1.1, June 2019

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

Apache Version 2.0

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.

Implementation language

C++

JavaScript

C++

Server operating systems

Illumos
Linux
OS X
Windows

hosted

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

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

via views

SQL

Support of SQL

SQL-like query language

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

View functions in JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

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

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

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

using specific database classes

User concepts

Access control

Access rights can be defined down to the item level

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