DBMS > Cloudflare Workers KV vs. Dragonfly vs. HarperDB vs. SQLite

System Properties Comparison Cloudflare Workers KV vs. Dragonfly vs. HarperDB vs. SQLite

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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.

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

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Document store

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	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

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

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

www.harperdb.io

www.sqlite.org

Technical documentation

developers.cloudflare.com/kv/api

www.dragonflydb.io/docs

docs.harperdb.io/docs

www.sqlite.org/docs.html

Developer

Cloudflare

DragonflyDB team and community contributors

HarperDB

Dwayne Richard Hipp

Initial release

2018

2023

2017

2000

Current release

1.0, March 2023

3.1, August 2021

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

free community edition available

Open Source

Public Domain

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++

Node.js

Server operating systems

hosted

Linux

Linux
OS X

server-less

Data scheme

schema-free

scheme-free

dynamic schema

yes

dynamic column types

Typing

predefined data types such as float or date

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

yes

JSON data types

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP REST
Proprietary protocol

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

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
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Custom Functions

since release 3.1

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate 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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access rights for users and roles

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