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

System Properties Comparison Amazon Redshift vs. Graph Engine vs. HBase 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 in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Wide-column store based on Apache Hadoop and on concepts of BigTable

JavaScript DBMS with an API inspired by CouchDB

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Wide column store

Document store

Native XML DBMS
Search engine

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

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

Score	27.97
Rank	#26	Overall
	#2	Wide column 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.graphengine.io

hbase.apache.org

pouchdb.com

www.searchxml.net/category/products

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

hbase.apache.org/book.html

pouchdb.com/guides

www.searchxml.net/support/handouts

Developer

Amazon (based on PostgreSQL)

Microsoft

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

informationpartners gmbh

Initial release

2012

2010

2008

2012

2015

Current release

2.3.4, January 2021

7.1.1, June 2019

1.0

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache version 2

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

.NET and C

Java

JavaScript

C++

Server operating systems

hosted

.NET

Linux
Unix
Windows

using Cygwin

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

Windows

Data scheme

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

View functions in JavaScript

yes

on the application server

Triggers

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
Source-replica replication

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

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