DBMS > AllegroGraph vs. Hawkular Metrics vs. Microsoft Azure Cosmos DB vs. Quasardb vs. Yaacomo

System Properties Comparison AllegroGraph vs. Hawkular Metrics vs. Microsoft Azure Cosmos DB vs. Quasardb vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

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

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

allegrograph.com

www.hawkular.org

azure.microsoft.com/services/cosmos-db

quasar.ai

yaacomo.com

Technical documentation

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

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

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

Developer

Franz Inc.

Community supported by Red Hat

Microsoft

quasardb

Q2WEB GmbH

Initial release

2004

2014

2009

Current release

8.0, December 2023

3.14.1, January 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Linux
OS X
Windows

hosted

BSD
Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

RDF schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

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

yes

with tags

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

HTTP REST

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

HTTP API

JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Go
Java
Python
Ruby

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

JavaScript

Triggers

yes

via Hawkular Alerting

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

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

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
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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