DBMS > Hawkular Metrics vs. MonetDB vs. Sphinx vs. WakandaDB

System Properties Comparison Hawkular Metrics vs. MonetDB vs. Sphinx vs. WakandaDB

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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.

A relational database management system that stores data in columns

Open source search engine for searching in data from different sources, e.g. relational databases

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

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

www.monetdb.org/Documentation

sphinxsearch.com/docs

wakanda.github.io/doc

Developer

Community supported by Red Hat

MonetDB BV

Sphinx Technologies Inc.

Wakanda SAS

Initial release

2014

2004

2001

2012

Current release

Dec2023 (11.49), December 2023

3.5.1, February 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

GPL version 2, commercial licence available

Open Source

AGPLv3, extended commercial license available

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++

C++, JavaScript

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL 2003 with some extensions

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP REST

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Proprietary protocol

RESTful HTTP API

Supported programming languages

Go
Java
Python
Ruby

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding via remote tables

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Source-replica replication available in experimental status

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

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

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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