DBMS > Hawkular Metrics vs. JanusGraph vs. Microsoft Access vs. MySQL vs. Prometheus

System Properties Comparison Hawkular Metrics vs. JanusGraph vs. Microsoft Access vs. MySQL vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

www.hawkular.org

janusgraph.org

www.microsoft.com/en-us/microsoft-365/access

www.mysql.com

prometheus.io

Technical documentation

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

docs.janusgraph.org

developer.microsoft.com/en-us/access

dev.mysql.com/doc

prometheus.io/docs

Developer

Community supported by Red Hat

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

2017

1992

1995

2015

Current release

0.6.3, February 2023

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

HTTP REST

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python
Ruby

Clojure
Java
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

via Hawkular Alerting

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

none

Multi-source replication
Source-replica replication

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

but no files for transaction logging

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

User authentification and security via Rexster Graph Server

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

no user groups or roles

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