DBMS > Dragonfly vs. Fujitsu Enterprise Postgres vs. OushuDB

System Properties Comparison Dragonfly vs. Fujitsu Enterprise Postgres vs. OushuDB

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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

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.51
Rank	#245	Overall
	#35	Key-value stores

Score	0.23
Rank	#297	Overall
	#133	Relational DBMS

Score	0.00
Rank	#378	Overall
	#154	Relational DBMS

Website

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

www.postgres.global.fujitsu.com

www.oushu.com/product/oushuDB

Technical documentation

www.dragonflydb.io/docs

www.postgres.global.fujitsu.com/product-manuals

www.oushu.com/documentation

Developer

DragonflyDB team and community contributors

Fujitsu Limited

Oushu

Initial release

2023

Current release

1.0, March 2023

Fujitsu Enterprise Postgres 16, May 2024

4.0.1, August 2020

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux

Linux
Windows

Linux

Data scheme

scheme-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

Full-featured ANSI SQL support

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

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++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++

Server-side scripts

Stored procedures

Lua

user defined functions

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Password-based authentication

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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