DBMS > Amazon Redshift vs. Coveo vs. Graph Engine vs. IBM Db2 vs. Riak KV

System Properties Comparison Amazon Redshift vs. Coveo vs. Graph Engine vs. IBM Db2 vs. Riak KV

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Common in IBM host environments, 2 different versions for host and Windows/Linux

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Search engine

Graph DBMS
Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

aws.amazon.com/redshift

www.coveo.com

www.graphengine.io

www.ibm.com/products/db2

Technical documentation

docs.aws.amazon.com/redshift

docs.coveo.com

www.graphengine.io/docs/manual

www.ibm.com/docs/en/db2

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Amazon (based on PostgreSQL)

Coveo

Microsoft

IBM

OpenSource, formerly Basho Technologies

Initial release

2012

2010

1983

host version

2009

Current release

12.1, October 2016

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

free version is available

Open Source

Apache version 2, commercial enterprise edition

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

.NET and C

C and C++

Erlang

Server operating systems

hosted

.NET

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X

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

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

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

C#
C++
F#
Visual Basic

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

Sharding

only with Windows/Unix/Linux Version

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

links between data sets can be stored

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

yes, using Riak Security

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