DBMS > Badger vs. Dragonfly vs. mSQL vs. SWC-DB

System Properties Comparison Badger vs. Dragonfly vs. mSQL vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

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

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

github.com/dgraph-io/badger

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

hughestech.com.au/products/msql

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.dragonflydb.io/docs

Developer

DGraph Labs

DragonflyDB team and community contributors

Hughes Technologies

Alex Kashirin

Initial release

2017

2023

1994

2020

Current release

1.0, March 2023

4.4, October 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSL 1.1

commercial

free licenses can be provided

Open Source

GPL V3

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.

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Data scheme

schema-free

scheme-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

Proprietary protocol
Thrift

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++
Delphi
Java
Perl
PHP
Tcl

C++

Server-side scripts

Stored procedures

Lua

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

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

User concepts

Access control

Password-based authentication

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