DBMS > Dragonfly vs. Microsoft Azure SQL Database vs. PouchDB vs. SQLite

System Properties Comparison Dragonfly vs. Microsoft Azure SQL Database vs. PouchDB vs. SQLite

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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

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

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

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	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

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

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

pouchdb.com

www.sqlite.org

Technical documentation

www.dragonflydb.io/docs

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

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

DragonflyDB team and community contributors

Microsoft

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2023

2010

2012

2000

Current release

1.0, March 2023

V12

7.1.1, June 2019

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

JavaScript

Server operating systems

Linux

hosted

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

server-less

Data scheme

scheme-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

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

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Lua

Transact SQL

View functions in JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with always 3 replicas available

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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