DBMS > Amazon Redshift vs. Apache Impala vs. Infobright vs. SiteWhere vs. VoltDB

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Infobright vs. SiteWhere vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

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

M2M integration platform for persisting/querying time series data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Time Series DBMS

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	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

ignitetech.com/softwarelibrary/infobrightdb

github.com/sitewhere/sitewhere

www.voltdb.com

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

sitewhere1.sitewhere.io/index.html

docs.voltdb.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Ignite Technologies Inc.; formerly InfoBright Inc.

SiteWhere

VoltDB Inc.

Initial release

2012

2013

2005

2010

Current release

4.1.0, June 2022

11.3, April 2022

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

Common Public Attribution License Version 1.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java

Java, C++

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

yes

predefined 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.

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

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP REST

Java API
JDBC
RESTful HTTP/JSON API

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

Users and roles with access to stored procedures

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