DBMS > Amazon Redshift vs. ArangoDB vs. Coveo vs. Realm vs. Trafodion

System Properties Comparison Amazon Redshift vs. ArangoDB vs. Coveo vs. Realm vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Search engine

Search engine

Document store

Relational DBMS

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

Score	14.07
Rank	#38	Overall
	#23	Relational DBMS

Score	3.09
Rank	#83	Overall
	#15	Document stores
	#5	Graph DBMS
	#11	Key-value stores
	#10	Search engines

Score	2.32
Rank	#109	Overall
	#11	Search engines

Score	7.05
Rank	#49	Overall
	#8	Document stores

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.arangodb.com

docs.coveo.com

realm.io/docs

trafodion.apache.org/documentation.html

Developer

Amazon (based on PostgreSQL)

ArangoDB Inc.

Coveo

Realm, acquired by MongoDB in May 2019

Apache Software Foundation, originally developed by HP

Initial release

2012

2014

Current release

3.11.5, November 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial

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

Server operating systems

hosted

Linux
OS X
Windows

hosted

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

yes

schema-free

automatically recognizes schema within a collection

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

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

C#
Java
JavaScript
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in Python

JavaScript

runs within the applications so server-side scripts are unnecessary

Java Stored Procedures

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with configurable replication factor

yes

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

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

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

yes

granular access controls, API key management, content filters

yes

fine grained access rights according to SQL-standard

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