DBMS > Amazon Redshift vs. CouchDB vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable

System Properties Comparison Amazon Redshift vs. CouchDB vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

An open source BigTable implementation based on distributed file systems such as Hadoop

Primary database model

Relational DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Wide column store

Secondary database models

Spatial DBMS

using the Geocouch extension

Graph DBMS
Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Website

aws.amazon.com/redshift

couchdb.apache.org

firebase.google.com/products/realtime-database

www.gigaspaces.com

Technical documentation

docs.aws.amazon.com/redshift

docs.couchdb.org/en/stable

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

acquired by Google 2014

Gigaspaces Technologies

Hypertable Inc.

Initial release

2012

2005

2012

2000

2009

Current release

3.3.3, December 2023

15.5, September 2020

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

GNU version 3. Commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java, C++, .Net

C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

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.

XML can be used for describing objects metadata

Secondary indexes

restricted

yes

via views

yes

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

limited functionality with using 'rules'

yes

Triggers

yes

Callbacks are triggered when data changes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

atomic operations within a single document possible

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

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 rights for users can be defined per database

yes, based on authentication and database rules

Role-based access control

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