DBMS > Lovefield vs. Microsoft Azure Cosmos DB vs. OpenMLDB vs. OpenQM vs. PouchDB

System Properties Comparison Lovefield vs. Microsoft Azure Cosmos DB vs. OpenMLDB vs. OpenQM vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Globally distributed, horizontally scalable, multi-model database service

An open-source machine learning database that provides a feature platform for training and inference

QpenQM is a high-performance, self-tuning, multi-value DBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Multivalue DBMS

Document store

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

openmldb.ai

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

pouchdb.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

learn.microsoft.com/azure/cosmos-db

openmldb.ai/docs/zh/main

pouchdb.com/guides

Developer

Google

Microsoft

4 Paradigm Inc.

Rocket Software, originally Martin Phillips

Apache Software Foundation

Initial release

2014

2020

1993

2012

Current release

2.1.12, February 2017

2024-2 February 2024

3.4-12

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

Open Source

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

JavaScript

C++, Java, Scala

JavaScript

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

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

Data scheme

yes

schema-free

Fixed schema

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

via views

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

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

JDBC
SQLAlchemy

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

JavaScript

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

C++
Go
Java
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript

Server-side scripts

Stored procedures

JavaScript

yes

View functions in JavaScript

Triggers

Using read-only observers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Source-replica replication

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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