DBMS > Infobright vs. IRONdb vs. Quasardb vs. STSdb

System Properties Comparison Infobright vs. IRONdb vs. Quasardb vs. STSdb

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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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

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

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

ignitetech.com/softwarelibrary/infobrightdb

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

quasar.ai

github.com/STSSoft/STSdb4

Technical documentation

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

doc.quasar.ai/master

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Circonus LLC.

quasardb

STS Soft SC

Initial release

2005

2017

2009

2011

Current release

V0.10.20, January 2018

3.14.1, January 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, commercial license available

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++

Server operating systems

Linux
Windows

Linux

BSD
Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

integer and binary

yes

primitive types and user defined types (classes)

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

Knowledge Grid Technology used instead

yes

with tags

SQL

Support of SQL

yes

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

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

.NET Client API

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

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

C#
Java

Server-side scripts

Stored procedures

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

configurable replication factor, datacenter aware

Source-replica replication with selectable replication factor

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

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Cryptographically strong user authentication and audit trail

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