DBMS > Amazon Redshift vs. Elasticsearch vs. Graph Engine vs. PouchDB vs. searchxml

System Properties Comparison Amazon Redshift vs. Elasticsearch vs. Graph Engine vs. PouchDB vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

JavaScript DBMS with an API inspired by CouchDB

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Search engine

Graph DBMS
Key-value store

Document store

Native XML DBMS
Search engine

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

aws.amazon.com/redshift

www.elastic.co/elasticsearch

www.graphengine.io

pouchdb.com

www.searchxml.net/category/products

Technical documentation

docs.aws.amazon.com/redshift

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

www.graphengine.io/docs/manual

pouchdb.com/guides

www.searchxml.net/support/handouts

Developer

Amazon (based on PostgreSQL)

Elastic

Microsoft

Apache Software Foundation

informationpartners gmbh

Initial release

2012

2010

2012

2015

Current release

8.6, January 2023

7.1.1, June 2019

1.0

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

MIT License

Open Source

commercial

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

Java

.NET and C

JavaScript

C++

Server operating systems

hosted

All OS with a Java VM

.NET

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

Windows

Data scheme

yes

schema-free

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

yes

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

restricted

yes

All search fields are automatically indexed

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
F#
Visual Basic

JavaScript

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

in Python

yes

View functions in JavaScript

yes

on the application server

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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