DBMS > Dragonfly vs. Sadas Engine vs. SWC-DB vs. Ultipa

System Properties Comparison Dragonfly vs. Sadas Engine vs. SWC-DB vs. Ultipa

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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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high performance, scalable Wide Column DBMS

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Secondary database models

Time Series DBMS

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

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

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

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

www.sadasengine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.ultipa.com

Technical documentation

www.dragonflydb.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.ultipa.com/document

Developer

DragonflyDB team and community contributors

SADAS s.r.l.

Alex Kashirin

Ultipa

Initial release

2023

2006

2020

2019

Current release

1.0, March 2023

8.0

0.5, April 2021

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

free trial version available

Open Source

GPL V3

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

AIX
Linux
Windows

Linux

Data scheme

scheme-free

yes

schema-free

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

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

RESTful HTTP 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#
C++
Groovy
Java
PHP
Python

C++

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

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

managed by 'Learn by Usage'

User concepts

Access control

Password-based authentication

Access rights for users, groups and roles according to SQL-standard

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