DBMS > AllegroGraph vs. Coveo vs. Microsoft Azure Cosmos DB vs. Oracle Coherence

System Properties Comparison AllegroGraph vs. Coveo vs. Microsoft Azure Cosmos DB vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

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

Globally distributed, horizontally scalable, multi-model database service

Oracles in-memory data grid solution

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

allegrograph.com

www.coveo.com

azure.microsoft.com/services/cosmos-db

www.oracle.com/java/coherence

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.coveo.com

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/middleware/standalone/coherence

Developer

Franz Inc.

Coveo

Microsoft

Oracle

Initial release

2004

2012

2014

2007

Current release

8.0, December 2023

14.1, August 2023

License

Commercial or Open Source

commercial

Limited community edition free

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

Server operating systems

Linux
OS X
Windows

hosted

All OS with a Java VM

Data scheme

yes

RDF schemas

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

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

bulk load of XML files possible

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JCache
JPA
RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C#
Java
JavaScript
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C++
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

JavaScript

Triggers

yes

JavaScript

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

with Federation

yes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Multi-item ACID transactions with snapshot isolation within a partition

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

granular access controls, API key management, content filters

Access rights can be defined down to the item level

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

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23 May 2024

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17 April 2024

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3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

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