DBMS > Amazon Redshift vs. Firebase Realtime Database vs. Google Cloud Spanner vs. Graphite vs. OrigoDB

System Properties Comparison Amazon Redshift vs. Firebase Realtime Database vs. Google Cloud Spanner vs. Graphite vs. OrigoDB

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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

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	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Website

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

cloud.google.com/spanner

github.com/graphite-project/graphite-web

origodb.com

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

cloud.google.com/spanner/docs

graphite.readthedocs.io

origodb.com/docs

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

Google

Chris Davis

Robert Friberg et al

Initial release

2012

2017

2006

2009

under the name LiveDB

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

Python

Server operating systems

hosted

Linux
Unix

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Query statements complying to ANSI 2011

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

depending on model

Transaction concepts

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

ACID

yes

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

Write ahead log

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

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role based authorization

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