DBMS > Cloudflare Workers KV vs. Drizzle vs. mSQL vs. TDSQL for MySQL

System Properties Comparison Cloudflare Workers KV vs. Drizzle vs. mSQL vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

mSQL (Mini SQL) is a simple and lightweight RDBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

www.cloudflare.com/developer-platform/workers-kv

hughestech.com.au/products/msql

www.tencentcloud.com/products/dcdb

Technical documentation

developers.cloudflare.com/kv/api

www.tencentcloud.com/document/product/1042

Developer

Cloudflare

Drizzle project, originally started by Brian Aker

Hughes Technologies

Tencent

Initial release

2018

2008

1994

2013

Current release

7.2.4, September 2012

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

free licenses can be provided

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

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

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

with proprietary extensions

A subset of ANSI SQL is implemented

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

yes

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC

JDBC
ODBC

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C++
Java
PHP

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users with fine-grained authorization concept

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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