DBMS > Hawkular Metrics vs. MySQL vs. Sphinx vs. SwayDB vs. ToroDB

System Properties Comparison Hawkular Metrics vs. MySQL vs. Sphinx vs. SwayDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB 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.

Widely used open source RDBMS

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Search engine

Key-value store

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

github.com/torodb/server

Technical documentation

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

dev.mysql.com/doc

sphinxsearch.com/docs

Developer

Community supported by Red Hat

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Simer Plaha

8Kdata

Initial release

2014

1995

2001

2018

2016

Current release

8.4.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Open Source

GNU Affero GPL V3.0

Open Source

AGPL-V3

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.

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Implementation language

Java

C and C++

C++

Scala

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Supported programming languages

Go
Java
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
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
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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