DBMS > Hawkular Metrics vs. Infobright vs. Realm vs. Sequoiadb

System Properties Comparison Hawkular Metrics vs. Infobright vs. Realm vs. Sequoiadb

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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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS

Relational DBMS

Document store

Document store
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	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.hawkular.org

ignitetech.com/softwarelibrary/infobrightdb

realm.io

www.sequoiadb.com

Technical documentation

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

realm.io/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Community supported by Red Hat

Ignite Technologies Inc.; formerly InfoBright Inc.

Realm, acquired by MongoDB in May 2019

Sequoiadb Ltd.

Initial release

2014

2005

2014

2013

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Server: AGPL; Client: Apache V2

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.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

JavaScript

Triggers

yes

via Hawkular Alerting

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

Source-replica replication

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Document is locked during a transaction

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

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

simple password-based access control

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More resources

DB-Engines blog posts

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2 March 2016, Paul Andlinger

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