DBMS > IRONdb vs. MySQL vs. PostGIS vs. SAP IQ vs. SiriDB

System Properties Comparison IRONdb vs. MySQL vs. PostGIS vs. SAP IQ vs. SiriDB

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

Widely used open source RDBMS

Spatial extension of PostgreSQL

Columnar RDBMS optimized for Big Data analytics

Open Source Time Series DBMS

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Relational DBMS

column-oriented

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

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

www.mysql.com

postgis.net

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

siridb.com

Technical documentation

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

dev.mysql.com/doc

postgis.net/documentation

help.sap.com/docs/SAP_IQ

docs.siridb.com

Developer

Circonus LLC.

Oracle

since 2010, originally MySQL AB, then Sun

SAP, formerly Sybase

Cesbit

Initial release

2017

1995

2005

1994

2017

Current release

V0.10.20, January 2018

8.4.0, April 2024

3.4.2, February 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL v2.0

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

Numeric data

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)

yes

with proprietary extensions

yes

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

.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

C
C#
C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes, in Lua

yes

proprietary syntax

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

based on PostgreSQL

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

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 capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

simple rights management via user accounts

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