DBMS > Dragonfly vs. Ignite vs. KairosDB vs. MySQL

System Properties Comparison Dragonfly vs. Ignite vs. KairosDB vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Distributed Time Series DBMS based on Cassandra or H2

Widely used open source RDBMS

Primary database model

Key-value store

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

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

ignite.apache.org

github.com/kairosdb/kairosdb

www.mysql.com

Technical documentation

www.dragonflydb.io/docs

apacheignite.readme.io/docs

kairosdb.github.io

dev.mysql.com/doc

Developer

DragonflyDB team and community contributors

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2023

2015

2013

1995

Current release

1.0, March 2023

Apache Ignite 2.6

1.2.2, November 2018

8.4.0, April 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C++, Java, .Net

Java

C and C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

scheme-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

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

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax

Triggers

publish/subscribe channels provide some trigger functionality

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

table locks or row locks depending on storage engine

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

Password-based authentication

Security Hooks for custom implementations

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

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