DBMS > Amazon Redshift vs. Coveo vs. GridGain vs. Hawkular Metrics vs. Infobright

System Properties Comparison Amazon Redshift vs. Coveo vs. GridGain vs. Hawkular Metrics vs. Infobright

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

GridGain is an in-memory computing platform, built on Apache Ignite

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

Primary database model

Relational DBMS

Search engine

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Website

aws.amazon.com/redshift

www.coveo.com

www.gridgain.com

www.hawkular.org

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

docs.aws.amazon.com/redshift

docs.coveo.com

www.gridgain.com/docs/index.html

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

Developer

Amazon (based on PostgreSQL)

Coveo

GridGain Systems, Inc.

Community supported by Red Hat

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2012

2007

2014

2005

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

commercial, open source

Open Source

Apache 2.0

commercial

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

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++, .Net, Python, REST, SQL

Java

Server operating systems

hosted

Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Go
Java
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

yes

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

granular access controls, API key management, content filters

Role-based access control
Security Hooks for custom implementations

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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