DBMS > Amazon Redshift vs. Greenplum vs. Immudb vs. Microsoft Azure SQL Database

System Properties Comparison Amazon Redshift vs. Greenplum vs. Immudb vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Website

aws.amazon.com/redshift

greenplum.org

github.com/codenotary/immudb
immudb.io

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

docs.aws.amazon.com/redshift

docs.greenplum.org

docs.immudb.io

docs.microsoft.com/en-us/azure/azure-sql

Developer

Amazon (based on PostgreSQL)

Pivotal Software Inc.

Codenotary

Microsoft

Initial release

2012

2005

2020

2010

Current release

7.0.0, September 2023

1.2.3, April 2022

V12

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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++

Server operating systems

hosted

Linux

BSD
Linux
macOS
Solaris
Windows
z/OS

hosted

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

since Version 4.2

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like syntax

yes

APIs and other access methods

JDBC
ODBC

gRPC protocol
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
Java
Perl
Python
R

.Net
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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