DBMS > Citus vs. Dragonfly vs. Sadas Engine vs. SiriDB vs. SiteWhere

System Properties Comparison Citus vs. Dragonfly vs. Sadas Engine vs. SiriDB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Open Source Time Series DBMS

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Document store

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

Score	2.15
Rank	#123	Overall
	#60	Relational DBMS

Score	0.42
Rank	#271	Overall
	#38	Key-value stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	0.11
Rank	#346	Overall
	#32	Time Series DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

www.citusdata.com

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

www.sadasengine.com

siridb.com

github.com/sitewhere/sitewhere

Technical documentation

docs.citusdata.com

www.dragonflydb.io/docs

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

docs.siridb.com

sitewhere1.sitewhere.io/index.html

Developer

DragonflyDB team and community contributors

SADAS s.r.l.

Cesbit

SiteWhere

Initial release

2010

2023

2006

2017

2010

Current release

8.1, December 2018

1.0, March 2023

8.0

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

BSL 1.1

commercial

free trial version available

Open Source

MIT License

Open Source

Common Public Attribution License Version 1.0

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++

Java

Server operating systems

Linux

AIX
Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

scheme-free

yes

predefined scheme

Typing

predefined data types such as float or date

yes

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

yes

Numeric data

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

APIs and other access methods

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

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Proprietary protocol

HTTP API

HTTP REST

Supported programming languages

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

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)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Lua

Triggers

yes

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

none

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Concurrency

Support for concurrent manipulation of data

yes

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'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

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

simple rights management via user accounts

Users with fine-grained authorization concept

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