DBMS > atoti vs. DataFS vs. Dragonfly

System Properties Comparison atoti vs. DataFS vs. Dragonfly

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Primary database model

Object oriented DBMS

Key-value store

Secondary database models

Graph DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

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

Website

atoti.io

newdatabase.com

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

Technical documentation

docs.atoti.io

dev.mobiland.com/Overview.xsp

www.dragonflydb.io/docs

Developer

ActiveViam

Mobiland AG

DragonflyDB team and community contributors

Initial release

2018

2023

Current release

1.1.263, October 2022

1.0, March 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

BSL 1.1

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

Java

C++

Server operating systems

Windows

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

scheme-free

Typing

predefined data types such as float or date

yes

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

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

.Net
C
C#
C++
VB.Net

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

Server-side scripts

Stored procedures

Python

Lua

Triggers

no, except callback-events from server when changes happened

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Proprietary Sharding system

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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, multi-version concurrency control (MVCC)

yes

yes, strict serializability by the server

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

Windows-Profile

Password-based authentication

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More resources

Recent citations in the news

Best use of cloud: ActiveViam
28 November 2023, Risk.net

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provided by Google News

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