DBMS > IRONdb vs. Kingbase vs. Prometheus vs. RDF4J

System Properties Comparison IRONdb vs. Kingbase vs. Prometheus 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

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Open-source Time Series DBMS and monitoring system

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

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

www.kingbase.com.cn

prometheus.io

rdf4j.org

Technical documentation

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

prometheus.io/docs

rdf4j.org/documentation

Developer

Circonus LLC.

BeiJing KINGBASE Information technologies inc.

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

Initial release

2017

1999

2015

2004

Current release

V0.10.20, January 2018

V8.0, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache 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

C and C++

C and Java

Java

Server operating systems

Linux

Linux
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

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

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

Standard with numerous extensions

APIs and other access methods

HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

RESTful HTTP/JSON API

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

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

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 per node, eventual consistency across nodes

Immediate Consistency

none

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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