DBMS > Dragonfly vs. Kingbase vs. TerarkDB vs. VoltDB

System Properties Comparison Dragonfly vs. Kingbase vs. TerarkDB vs. VoltDB

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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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

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

www.kingbase.com.cn

github.com/bytedance/terarkdb

www.voltdb.com

Technical documentation

www.dragonflydb.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.voltdb.com

Developer

DragonflyDB team and community contributors

BeiJing KINGBASE Information technologies inc.

ByteDance, originally Terark

VoltDB Inc.

Initial release

2023

1999

2016

2010

Current release

1.0, March 2023

V8.0, August 2021

11.3, April 2022

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

restricted open source version available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

C and Java

C++

Java, C++

Server operating systems

Linux

Linux
Windows

Linux
OS X

for development

Data scheme

scheme-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

only a subset of SQL 99

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

C++ API
Java API

Java API
JDBC
RESTful HTTP/JSON 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

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C++
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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