DBMS > Amazon Redshift vs. Apache Impala vs. Atos Standard Common Repository vs. Infobright vs. Quasardb

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Atos Standard Common Repository vs. Infobright vs. Quasardb

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/redshift

impala.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

ignitetech.com/softwarelibrary/infobrightdb

quasar.ai

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

doc.quasar.ai/master

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Ignite Technologies Inc.; formerly InfoBright Inc.

quasardb

Initial release

2012

2013

2016

2005

2009

Current release

4.1.0, June 2022

1703

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

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

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++

Java

C++

Server operating systems

hosted

Linux

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

Secondary indexes

restricted

yes

Knowledge Grid Technology used instead

yes

with tags

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

LDAP

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

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

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

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

Atomic execution of specific operations

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Cryptographically strong user authentication and audit trail

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