DBMS > Amazon Redshift vs. Microsoft Azure Table Storage vs. Prometheus vs. ReductStore

System Properties Comparison Amazon Redshift vs. Microsoft Azure Table Storage vs. Prometheus vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A Wide Column Store for rapid development using massive semi-structured datasets

Open-source Time Series DBMS and monitoring system

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS

Wide column store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

aws.amazon.com/redshift

azure.microsoft.com/en-us/services/storage/tables

prometheus.io

github.com/reductstore
www.reduct.store

Technical documentation

docs.aws.amazon.com/redshift

prometheus.io/docs

www.reduct.store/docs

Developer

Amazon (based on PostgreSQL)

Microsoft

ReductStore LLC

Initial release

2012

2015

2023

Current release

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Business Source License 1.1

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++, Rust

Server operating systems

hosted

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

RESTful HTTP/JSON API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

optimistic locking

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

Access rights based on private key authentication or shared access signatures

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