DBMS > Hawkular Metrics vs. ITTIA vs. Microsoft SQL Server vs. Quasardb vs. Realm

System Properties Comparison Hawkular Metrics vs. ITTIA vs. Microsoft SQL Server vs. Quasardb vs. Realm

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.

Edge Time Series DBMS with Real-Time Stream Processing

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

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

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

www.hawkular.org

www.ittia.com

www.microsoft.com/en-us/sql-server

quasar.ai

realm.io

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

doc.quasar.ai/master

realm.io/docs

Developer

Community supported by Red Hat

ITTIA L.L.C.

Microsoft

quasardb

Realm, acquired by MongoDB in May 2019

Initial release

2014

2007

1989

2009

2014

Current release

8.7

SQL Server 2022, November 2022

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

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

Open Source

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 and C++

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

Fixed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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.

yes

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST

JDBC
ODBC
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API

Supported programming languages

Go
Java
Python
Ruby

C
C++
JavaScript (Node.js)
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via Hawkular Alerting

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

In-Memory realm

User concepts

Access control

Database file passwords

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

yes

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