DBMS > BoltDB vs. Hive vs. MonetDB vs. MySQL vs. RRDtool

System Properties Comparison BoltDB vs. Hive vs. MonetDB vs. MySQL vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A relational database management system that stores data in columns

Widely used open source RDBMS

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

Key-value store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

github.com/boltdb/bolt

hive.apache.org

www.monetdb.org

www.mysql.com

oss.oetiker.ch/rrdtool

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

www.monetdb.org/Documentation

dev.mysql.com/doc

oss.oetiker.ch/rrdtool/doc

Developer

Apache Software Foundation

initially developed by Facebook

MonetDB BV

Oracle

since 2010, originally MySQL AB, then Sun

Tobias Oetiker

Initial release

2013

2012

2004

1995

1999

Current release

3.1.3, April 2022

Dec2023 (11.49), December 2023

8.4.0, April 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2

Open Source

Mozilla Public License 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

HP-UX
Linux

Data scheme

schema-free

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL 2003 with some extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

in-process shared library
Pipes

Supported programming languages

C++
Java
PHP
Python

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

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

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

user defined functions and integration of map-reduce

yes, in SQL, C, R

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding via remote tables

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

yes

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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