DBMS > Amazon Redshift vs. Infobright vs. IRONdb vs. Sqrrl vs. ToroDB

System Properties Comparison Amazon Redshift vs. Infobright vs. IRONdb vs. Sqrrl vs. ToroDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

Adaptable, secure NoSQL built on Apache Accumulo

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Website

aws.amazon.com/redshift

ignitetech.com/softwarelibrary/infobrightdb

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

sqrrl.com

github.com/torodb/server

Technical documentation

docs.aws.amazon.com/redshift

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

Developer

Amazon (based on PostgreSQL)

Ignite Technologies Inc.; formerly InfoBright Inc.

Circonus LLC.

Amazon

originally Sqrrl Data, Inc.

8Kdata

Initial release

2012

2005

2017

2012

2016

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

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

commercial

Open Source

AGPL-V3

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

hosted

Linux
Windows

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

string, integer, double, boolean, date, object_id

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

restricted

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

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

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

.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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic, metric affinity per node

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

configurable replication factor, datacenter aware

selectable replication factor

making use of Hadoop

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

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