DBMS > Dragonfly vs. RocksDB vs. Tkrzw vs. Transwarp KunDB

System Properties Comparison Dragonfly vs. RocksDB vs. Tkrzw vs. Transwarp KunDB

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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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Key-value store

Relational DBMS

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

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

rocksdb.org

dbmx.net/tkrzw

www.transwarp.cn/en/product/kundb

Technical documentation

www.dragonflydb.io/docs

github.com/facebook/rocksdb/wiki

Developer

DragonflyDB team and community contributors

Facebook, Inc.

Mikio Hirabayashi

Transwarp

Initial release

2023

2013

2020

Current release

1.0, March 2023

9.2.1, May 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

BSD

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux

Linux
macOS

Data scheme

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

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

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

C++ API
Java API

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
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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.

yes

using specific database classes

User concepts

Access control

Password-based authentication

yes

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