DBMS > 4D vs. Dragonfly vs. DuckDB vs. Kdb vs. STSdb

System Properties Comparison 4D vs. Dragonfly vs. DuckDB vs. Kdb vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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 embeddable, in-process, column-oriented SQL OLAP RDBMS

High performance Time Series DBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Time Series DBMS
Vector DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.4d.com

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

duckdb.org

kx.com

github.com/STSSoft/STSdb4

Technical documentation

developer.4d.com

www.dragonflydb.io/docs

duckdb.org/docs

code.kx.com

Developer

4D, Inc

DragonflyDB team and community contributors

Kx Systems, a division of First Derivatives plc

STS Soft SC

Initial release

1984

2023

2018

2000

kdb was released 2000, kdb+ in 2003

2011

Current release

v20, April 2023

1.0, March 2023

0.10, February 2024

3.6, May 2018

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

MIT License

commercial

free 32-bit version

Open Source

GPLv2, commercial license available

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

OS X
Windows

Linux

server-less

Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

scheme-free

yes

Typing

predefined data types such as float or date

yes

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

yes

primitive types and user defined types (classes)

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

table attribute 'grouped'

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-like query language (q)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Proprietary protocol

RESP - REdis Serialization Protocol

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

.NET Client API

Supported programming languages

4D proprietary IDE
PHP

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#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes

Lua

user defined functions

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

with views

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Users and groups

Password-based authentication

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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