DBMS > Dragonfly vs. Microsoft Azure AI Search vs. MySQL vs. Quasardb vs. SiteWhere

System Properties Comparison Dragonfly vs. Microsoft Azure AI Search vs. MySQL vs. Quasardb vs. SiteWhere

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

Search-as-a-service for web and mobile app development

Widely used open source RDBMS

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Primary database model

Key-value store

Search engine

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

azure.microsoft.com/en-us/services/search

www.mysql.com

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

www.dragonflydb.io/docs

learn.microsoft.com/en-us/azure/search

dev.mysql.com/doc

doc.quasar.ai/master

sitewhere1.sitewhere.io/index.html

Developer

DragonflyDB team and community contributors

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

SiteWhere

Initial release

2023

2015

1995

2009

2010

Current release

1.0, March 2023

8.4.0, April 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Common Public Attribution License Version 1.0

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++

C and C++

C++

Java

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

scheme-free

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

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

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

HTTP REST

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

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Password-based authentication

yes

using Azure authentication

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

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