DBMS > Amazon Redshift vs. Postgres-XL vs. Prometheus vs. Quasardb

System Properties Comparison Amazon Redshift vs. Postgres-XL vs. Prometheus vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open-source Time Series DBMS and monitoring system

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/redshift

www.postgres-xl.org

prometheus.io

quasar.ai

Technical documentation

docs.aws.amazon.com/redshift

www.postgres-xl.org/documentation

prometheus.io/docs

doc.quasar.ai/master

Developer

Amazon (based on PostgreSQL)

quasardb

Initial release

2012

2014

since 2012, originally named StormDB

2015

2009

Current release

10 R1, October 2018

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

hosted

Linux
macOS

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

integer and binary

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

XML type, but no XML query functionality

Import of XML data possible

Secondary indexes

restricted

yes

with tags

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

distributed, parallel query execution

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

RESTful HTTP/JSON API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

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

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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