DBMS > Dragonfly vs. Sadas Engine vs. Transwarp KunDB vs. VictoriaMetrics

System Properties Comparison Dragonfly vs. Sadas Engine vs. Transwarp KunDB vs. VictoriaMetrics

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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

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

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

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

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

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

www.sadasengine.com

www.transwarp.cn/en/product/kundb

victoriametrics.com

Technical documentation

www.dragonflydb.io/docs

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

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

DragonflyDB team and community contributors

SADAS s.r.l.

Transwarp

VictoriaMetrics

Initial release

2023

2006

2018

Current release

1.0, March 2023

8.0

v1.91, May 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

free trial version available

commercial

Open Source

Apache Version 2.0

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

FreeBSD
Linux
macOS
OpenBSD

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Proprietary protocol

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Synchronous 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

Eventual 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

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

yes

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