DBMS > Dragonfly vs. EJDB vs. OrigoDB vs. Quasardb

System Properties Comparison Dragonfly vs. EJDB vs. OrigoDB vs. Quasardb

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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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A fully ACID in-memory object graph database

Distributed, high-performance timeseries database

Primary database model

Key-value store

Document store

Document store
Object oriented DBMS

Time Series DBMS

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

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

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

github.com/Softmotions/ejdb

origodb.com

quasar.ai

Technical documentation

www.dragonflydb.io/docs

github.com/Softmotions/ejdb/blob/master/README.md

origodb.com/docs

doc.quasar.ai/master

Developer

DragonflyDB team and community contributors

Softmotions

Robert Friberg et al

quasardb

Initial release

2023

2012

2009

under the name LiveDB

2009

Current release

1.0, March 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GPLv2

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

server-less

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

scheme-free

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

string, integer, double, bool, date, object_id

User defined using .NET types and collections

yes

integer and binary

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.

can be achieved using .NET

Secondary indexes

yes

with tags

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library

.NET Client API
HTTP API
LINQ

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

depending on model

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

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

Password-based authentication

Role based authorization

Cryptographically strong user authentication and audit trail

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