DBMS > Amazon Redshift vs. Firebase Realtime Database vs. Geode vs. NuoDB vs. OrientDB

System Properties Comparison Amazon Redshift vs. Firebase Realtime Database vs. Geode vs. NuoDB vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Graph DBMS
Key-value store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

geode.apache.org

www.3ds.com/nuodb-distributed-sql-database

orientdb.org

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

geode.apache.org/docs

doc.nuodb.com

www.orientdb.com/docs/last/index.html

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Dassault Systèmes

originally NuoDB, Inc.

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2002

2013

2010

Current release

1.1, February 2017

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

limited edition free

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (OQL)

yes

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

user defined functions

Java, SQL

Java, Javascript

Triggers

Callbacks are triggered when data changes

yes

Cache Event Listeners

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Managed transparently by NuoDB

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationship in graphs

Transaction concepts

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

ACID

yes

yes, on a single node

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights per client and object definable

Standard SQL roles/ privileges, Administrative Users

Access rights for users and roles; record level security configurable

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