DBMS > Amazon Redshift vs. Apache Impala vs. GBase vs. Infobright vs. Lovefield

System Properties Comparison Amazon Redshift vs. Apache Impala vs. GBase vs. Infobright vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational 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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

www.gbase.cn

ignitetech.com/softwarelibrary/infobrightdb

google.github.io/lovefield

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

General Data Technology Co., Ltd.

Ignite Technologies Inc.; formerly InfoBright Inc.

Google

Initial release

2012

2013

2004

2005

2014

Current release

4.1.0, June 2022

GBase 8a, GBase 8s, GBase 8c

2.1.12, February 2017

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

Open Source

Apache 2.0

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, Python

JavaScript

Server operating systems

hosted

Linux

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

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

Secondary indexes

restricted

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

Standard with numerous extensions

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

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

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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