DBMS > Hawkular Metrics vs. Microsoft Azure SQL Database vs. mSQL vs. Oracle vs. Titan

System Properties Comparison Hawkular Metrics vs. Microsoft Azure SQL Database vs. mSQL vs. Oracle vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

Database as a Service offering with high compatibility to Microsoft SQL Server

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used RDBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

www.hawkular.org

azure.microsoft.com/en-us/products/azure-sql/database

hughestech.com.au/products/msql

www.oracle.com/database

github.com/thinkaurelius/titan

Technical documentation

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

docs.microsoft.com/en-us/azure/azure-sql

docs.oracle.com/en/database

github.com/thinkaurelius/titan/wiki

Developer

Community supported by Red Hat

Microsoft

Hughes Technologies

Oracle

Aurelius, owned by DataStax

Initial release

2014

2010

1994

1980

2012

Current release

V12

4.4, October 2021

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

commercial

restricted free version is available

Open Source

Apache license, version 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

Java

C++

C and C++

Java

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Go
Java
Python
Ruby

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Clojure
Java
Python

Server-side scripts

Stored procedures

Transact SQL

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding, horizontal partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, with always 3 replicas available

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

Immediate Consistency

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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