DBMS > IRONdb vs. mSQL vs. RDF4J vs. Snowflake vs. TypeDB

System Properties Comparison IRONdb vs. mSQL vs. RDF4J vs. Snowflake vs. TypeDB

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Cloud-based data warehousing service for structured and semi-structured data

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

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

hughestech.com.au/products/msql

rdf4j.org

www.snowflake.com

typedb.com

Technical documentation

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

rdf4j.org/documentation

docs.snowflake.net/manuals/index.html

typedb.com/docs

Developer

Circonus LLC.

Hughes Technologies

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

Snowflake Computing Inc.

Vaticle

Initial release

2017

1994

2004

2014

2016

Current release

V0.10.20, January 2018

4.4, October 2021

2.26.3, January 2024

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Unix
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

HTTP API

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
JDBC
ODBC

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

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++
Delphi
Java
Perl
PHP
Tcl

Java
PHP
Python

JavaScript (Node.js)
Python

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes, in Lua

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

none

yes

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

none

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

none

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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