DBMS > Cloudflare Workers KV vs. DolphinDB vs. Graph Engine vs. mSQL

System Properties Comparison Cloudflare Workers KV vs. DolphinDB vs. Graph Engine vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Key-value store

Time Series DBMS
Vector DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.29
Rank	#283	Overall
	#40	Key-value stores

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Website

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

www.dolphindb.com

www.graphengine.io

hughestech.com.au/products/msql

Technical documentation

developers.cloudflare.com/kv/api

docs.dolphindb.cn/en/help200/index.html

www.graphengine.io/docs/manual

Developer

Cloudflare

DolphinDB, Inc

Microsoft

Hughes Technologies

Initial release

2018

2010

1994

Current release

v2.00.4, January 2022

4.4, October 2021

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

commercial

free licenses can be provided

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++

.NET and C

Server operating systems

hosted

Linux
Windows

.NET

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

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

SQL-like query language

A subset of ANSI SQL is implemented

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

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C#
C++
F#
Visual Basic

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Administrators, Users, Groups

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