DBMS > Amazon Redshift vs. Hawkular Metrics vs. Infobright vs. Machbase Neo vs. Microsoft Azure SQL Database

System Properties Comparison Amazon Redshift vs. Hawkular Metrics vs. Infobright vs. Machbase Neo vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Website

aws.amazon.com/redshift

www.hawkular.org

ignitetech.com/softwarelibrary/infobrightdb

machbase.com

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

Technical documentation

docs.aws.amazon.com/redshift

www.hawkular.org/hawkular-metrics/docs/user-guide

machbase.com/dbms

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

Developer

Amazon (based on PostgreSQL)

Community supported by Red Hat

Ignite Technologies Inc.; formerly InfoBright Inc.

Machbase

Microsoft

Initial release

2012

2014

2005

2013

2010

Current release

V8.0, August 2023

V12

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

commercial

free test version available

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

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

Linux
macOS
Windows

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

Secondary indexes

restricted

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
Python
Ruby

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication

selectable replication factor

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

simple password-based access control

fine grained access rights according to SQL-standard

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