DBMS > Amazon Redshift vs. Citus vs. Firebase Realtime Database vs. Geode vs. Linter

System Properties Comparison Amazon Redshift vs. Citus vs. Firebase Realtime Database vs. Geode vs. Linter

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

RDBMS for high security requirements

Primary database model

Secondary database models

Document store

Spatial DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	2.15
Rank	#123	Overall
	#60	Relational DBMS

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	1.99
Rank	#133	Overall
	#23	Key-value stores

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Website

aws.amazon.com/redshift

www.citusdata.com

firebase.google.com/products/realtime-database

geode.apache.org

linter.ru

Technical documentation

docs.aws.amazon.com/redshift

docs.citusdata.com

firebase.google.com/docs/database

geode.apache.org/docs

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.

relex.ru

Initial release

2012

2010

2012

2002

1990

Current release

8.1, December 2018

1.1, February 2017

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

C and C++

Server operating systems

hosted

Linux

hosted

All OS with a Java VM

the JDK (8 or later) is also required

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

yes

schema-free

yes

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

specific XML type available, but no XML query functionality

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

standard, with numerous extensions

SQL-like query language (OQL)

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Android
iOS
JavaScript API
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
JavaScript
Objective-C

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

limited functionality with using 'rules'

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Callbacks are triggered when data changes

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

ACID

yes

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

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

yes, based on authentication and database rules

Access rights per client and object definable

fine grained access rights according to SQL-standard

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