DBMS > Heroic vs. IRONdb vs. MonetDB vs. RDF4J

System Properties Comparison Heroic vs. IRONdb vs. MonetDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

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

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

A relational database management system that stores data in columns

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

Primary database model

Time Series DBMS

Relational DBMS

RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/spotify/heroic

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

www.monetdb.org

rdf4j.org

Technical documentation

spotify.github.io/heroic

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

www.monetdb.org/Documentation

rdf4j.org/documentation

Developer

Spotify

Circonus LLC.

MonetDB BV

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

Initial release

2014

2017

2004

Current release

V0.10.20, January 2018

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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 and C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

via Elasticsearch

yes

SQL

Support of SQL

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

yes

SQL 2003 with some extensions

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

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
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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