DBMS > Dragonfly vs. HEAVY.AI vs. MySQL vs. OrientDB

System Properties Comparison Dragonfly vs. HEAVY.AI vs. MySQL vs. OrientDB

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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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Widely used open source RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store

Secondary database models

Spatial DBMS

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	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

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

github.com/heavyai/heavydb
www.heavy.ai

www.mysql.com

orientdb.org

Technical documentation

www.dragonflydb.io/docs

docs.heavy.ai

dev.mysql.com/doc

www.orientdb.com/docs/last/index.html

Developer

DragonflyDB team and community contributors

HEAVY.AI, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

OrientDB LTD; CallidusCloud; SAP

Initial release

2023

2016

1995

2010

Current release

1.0, March 2023

5.10, January 2022

8.4.0, April 2024

3.2.29, March 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C++ and CUDA

C and C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

scheme-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

yes

with proprietary extensions

SQL-like query language, no joins

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON 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

All languages supporting JDBC/ODBC/Thrift
Python

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

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

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Java, Javascript

Triggers

publish/subscribe channels provide some trigger functionality

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationship in graphs

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles; record level security configurable

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