DBMS > Amazon CloudSearch vs. Amazon Redshift vs. Firebird vs. SQream DB

System Properties Comparison Amazon CloudSearch vs. Amazon Redshift vs. Firebird vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service for use with business intelligence tools

Firebird is an open source RDBMS forked from Borland's InterBase

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Search engine

Relational DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/redshift

www.firebirdsql.org

sqream.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/redshift

www.firebirdsql.org/en/reference-manuals

docs.sqream.com

Developer

Amazon

Amazon (based on PostgreSQL)

Firebird Foundation

SQream Technologies

Initial release

2012

2000

As fork of Borland's InterBase

2017

Current release

5.0.0, January 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

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

C and C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

all search fields are automatically indexed

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

HTTP API

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

.Net
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

PSQL

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

authentication via encrypted signatures

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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