DBMS > HEAVY.AI vs. mSQL vs. MySQL vs. Prometheus vs. RRDtool

System Properties Comparison HEAVY.AI vs. mSQL vs. MySQL vs. Prometheus vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

hughestech.com.au/products/msql

www.mysql.com

prometheus.io

oss.oetiker.ch/rrdtool

Technical documentation

docs.heavy.ai

dev.mysql.com/doc

prometheus.io/docs

oss.oetiker.ch/rrdtool/doc

Developer

HEAVY.AI, Inc.

Hughes Technologies

Oracle

since 2010, originally MySQL AB, then Sun

Tobias Oetiker

Initial release

2016

1994

1995

2015

1999

Current release

5.10, January 2022

4.4, October 2021

8.4.0, April 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

free licenses can be provided

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

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

C++ and CUDA

C and C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

HP-UX
Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

in-process shared library
Pipes

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

none

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

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

by using the rrdcached daemon

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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