DBMS > Amazon Redshift vs. Immudb vs. Infobright vs. openGauss

System Properties Comparison Amazon Redshift vs. Immudb vs. Infobright vs. openGauss

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Website

aws.amazon.com/redshift

github.com/codenotary/immudb
immudb.io

ignitetech.com/softwarelibrary/infobrightdb

gitee.com/opengauss
opengauss.org

Technical documentation

docs.aws.amazon.com/redshift

docs.immudb.io

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Amazon (based on PostgreSQL)

Codenotary

Ignite Technologies Inc.; formerly InfoBright Inc.

Huawei and openGauss community

Initial release

2012

2020

2005

2019

Current release

1.2.3, April 2022

3.0, March 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

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, C++, Java

Server operating systems

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
Windows

Linux

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.

Secondary indexes

restricted

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like syntax

yes

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC

gRPC protocol
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica 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

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

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users, groups and roles according to SQL-standard

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