DBMS > Hawkular Metrics vs. IRONdb vs. Microsoft SQL Server vs. Realm vs. SpatiaLite

System Properties Comparison Hawkular Metrics vs. IRONdb vs. Microsoft SQL Server vs. Realm vs. SpatiaLite

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Microsofts flagship relational DBMS

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

Spatial extension of SQLite

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.hawkular.org

www.circonus.com/solutions/time-series-database/

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

realm.io

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

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

realm.io/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Community supported by Red Hat

Circonus LLC.

Microsoft

Realm, acquired by MongoDB in May 2019

Alessandro Furieri

Initial release

2014

2017

1989

2014

2008

Current release

V0.10.20, January 2018

SQL Server 2022, November 2022

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Java

C and C++

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

Android
Backend: server-less
iOS
Windows

server-less

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

HTTP REST

HTTP API

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

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes, in Lua

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Automatic, metric affinity per node

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

configurable replication factor, datacenter aware

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.