DBMS > Amazon Redshift vs. Drizzle vs. EDB Postgres

System Properties Comparison Amazon Redshift vs. Drizzle vs. EDB Postgres

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Primary database model

Relational DBMS

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	2.18
Rank	#122	Overall
	#59	Relational DBMS

Website

aws.amazon.com/redshift

www.enterprisedb.com

Technical documentation

docs.aws.amazon.com/redshift

www.enterprisedb.com/docs

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

EnterpriseDB

Initial release

2012

2008

2005

Current release

7.2.4, September 2012

14, December 2021

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

BSD for PostgreSQL-components

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
Windows

Data scheme

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

with proprietary extensions

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC

JDBC

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

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C
C++
Delphi
Java
Perl
PHP
Python
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.

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

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

yes, multi-version concurrency control (MVCC)

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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