DBMS > IRONdb vs. Oracle NoSQL vs. RDFox vs. SQLite

System Properties Comparison IRONdb vs. Oracle NoSQL vs. RDFox vs. SQLite

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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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

High performance knowledge graph and semantic reasoning engine

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Document store
Key-value store
Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.oracle.com/database/nosql/technologies/nosql

www.oxfordsemantic.tech

www.sqlite.org

Technical documentation

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.oxfordsemantic.tech

www.sqlite.org/docs.html

Developer

Circonus LLC.

Oracle

Oxford Semantic Technologies

Dwayne Richard Hipp

Initial release

2017

2011

2017

2000

Current release

V0.10.20, January 2018

24.1, May 2024

6.0, Septermber 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

Public Domain

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++

Java

C++

Server operating systems

Linux

Linux
Solaris SPARC/x86

Linux
macOS
Windows

server-less

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

RDF schemas

yes

dynamic column types

Typing

predefined data types such as float or date

yes

text, numeric, histograms

optional

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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#
Go
Java
JavaScript (Node.js)
Python

C
Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

replication via a shared file system

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

off heap cache

yes

User concepts

Access control

Access rights for users and roles

Roles, resources, and access types

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