DBMS > Hive vs. IRONdb vs. MySQL vs. OpenTSDB vs. RDF4J

System Properties Comparison Hive vs. IRONdb vs. MySQL vs. OpenTSDB vs. RDF4J

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used open source RDBMS

Scalable Time Series DBMS based on HBase

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

hive.apache.org

www.circonus.com/solutions/time-series-database/

www.mysql.com

opentsdb.net

rdf4j.org

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

dev.mysql.com/doc

opentsdb.net/docs/build/html/index.html

rdf4j.org/documentation

Developer

Apache Software Foundation

initially developed by Facebook

Circonus LLC.

Oracle

since 2010, originally MySQL AB, then Sun

currently maintained by Yahoo and other contributors

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2017

1995

2011

2004

Current release

3.1.3, April 2022

V0.10.20, January 2018

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

LGPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C and C++

Java

Server operating systems

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

numeric data for metrics, strings for tags

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Java
PHP
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Erlang
Go
Java
Python
R
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in Lua

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

based on HBase

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

ACID

Isolation support depends on the API used

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

in-memory storage is supported as well

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

Users with fine-grained authorization concept

no user groups or roles

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