DBMS > Amazon Redshift vs. Dragonfly vs. IRONdb vs. Microsoft Azure SQL Database vs. Tkrzw

System Properties Comparison Amazon Redshift vs. Dragonfly vs. IRONdb vs. Microsoft Azure SQL Database vs. Tkrzw

Editorial information provided by DB-Engines

Name

IRONdb 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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Database as a Service offering with high compatibility to Microsoft SQL Server

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

aws.amazon.com/redshift

github.com/dragonflydb/dragonfly
www.dragonflydb.io

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

azure.microsoft.com/en-us/products/azure-sql/database

dbmx.net/tkrzw

Technical documentation

docs.aws.amazon.com/redshift

www.dragonflydb.io/docs

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

docs.microsoft.com/en-us/azure/azure-sql

Developer

Amazon (based on PostgreSQL)

DragonflyDB team and community contributors

Circonus LLC.

Microsoft

Mikio Hirabayashi

Initial release

2012

2023

2017

2010

2020

Current release

1.0, March 2023

V0.10.20, January 2018

V12

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

Open Source

Apache Version 2.0

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++

C and C++

C++

Server operating systems

hosted

Linux

hosted

Linux
macOS

Data scheme

yes

scheme-free

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes, in Lua

Transact SQL

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

configurable replication factor, datacenter aware

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

fine grained access rights according to SQL-standard

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