DBMS > Elasticsearch vs. Lovefield vs. OpenQM vs. PouchDB

System Properties Comparison Elasticsearch vs. Lovefield vs. OpenQM vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Embeddable relational database for web apps written in pure JavaScript

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	157.69
Rank	#8	Overall
	#1	Search engines

Score	0.23
Rank	#283	Overall
	#133	Relational DBMS

Score	0.23
Rank	#284	Overall
	#10	Multivalue DBMS

Score	3.09
Rank	#98	Overall
	#18	Document stores

Website

www.elastic.co/elasticsearch

google.github.io/lovefield

www.openqm.com

pouchdb.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

www.openqm.com/support/documentation

pouchdb.com/guides

Developer

Elastic

Google

Martin Phillips

Apache Software Foundation

Initial release

2010

2014

1993

2012

Current release

7.8.0, June 2020

2.1.12, February 2017

3.4-12

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

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.

Implementation language

Java

JavaScript

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

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

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

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 search fields are automatically indexed

yes

via views

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

by using the 'percolation' feature

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate 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

Durability

Support for making data persistent

yes

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.

Memcached and Redis integration

yes

using MemoryDB

yes

User concepts

Access control

Access rights can be defined down to the item level

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