DBMS > Dragonfly vs. Lovefield vs. MySQL vs. SiriDB vs. Trafodion

System Properties Comparison Dragonfly vs. Lovefield vs. MySQL vs. SiriDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Open Source Time Series DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.42
Rank	#271	Overall
	#38	Key-value stores

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.11
Rank	#346	Overall
	#32	Time Series DBMS

Website

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

google.github.io/lovefield

www.mysql.com

siridb.com

trafodion.apache.org

Technical documentation

www.dragonflydb.io/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

docs.siridb.com

trafodion.apache.org/documentation.html

Developer

DragonflyDB team and community contributors

Google

Oracle

since 2010, originally MySQL AB, then Sun

Cesbit

Apache Software Foundation, originally developed by HP

Initial release

2023

2014

1995

2017

2014

Current release

1.0, March 2023

2.1.12, February 2017

8.3.0, January 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

MIT License

Open Source

Apache 2.0

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.

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Implementation language

C++

JavaScript

C and C++

C++, Java

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

scheme-free

yes

Typing

predefined data types such as float or date

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

yes

Numeric data

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

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

ADO.NET
JDBC
ODBC

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

JavaScript

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

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Java Stored Procedures

Triggers

publish/subscribe channels provide some trigger functionality

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Password-based authentication

Users with fine-grained authorization concept

no user groups or roles

simple rights management via user accounts

fine grained access rights according to SQL-standard

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