DBMS > Hawkular Metrics vs. Percona Server for MongoDB vs. Riak KV vs. Trafodion

System Properties Comparison Hawkular Metrics vs. Percona Server for MongoDB vs. Riak KV vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. 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 drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, fault tolerant key-value store

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	0.52
Rank	#254	Overall
	#39	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.hawkular.org

www.percona.com/mongodb/software/percona-server-for-mongodb

trafodion.apache.org

Technical documentation

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

docs.percona.com/percona-distribution-for-mongodb

www.tiot.jp/riak-docs/riak/kv/latest

trafodion.apache.org/documentation.html

Developer

Community supported by Red Hat

Percona

OpenSource, formerly Basho Technologies

Apache Software Foundation, originally developed by HP

Initial release

2014

2015

2009

2014

Current release

3.4.10-2.10, November 2017

3.2.0, December 2022

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL Version 2

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache 2.0

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++

Erlang

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

Linux

Data scheme

schema-free

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

proprietary protocol using JSON

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
Python
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

JavaScript

Erlang

Java Stored Procedures

Triggers

yes

via Hawkular Alerting

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

selectable replication factor

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

via In-Memory Engine

User concepts

Access control

Access rights for users and roles

yes, using Riak Security

fine grained access rights according to SQL-standard

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