DBMS > Dragonfly vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. TinkerGraph

System Properties Comparison Dragonfly vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. TinkerGraph

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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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Globally distributed, horizontally scalable, multi-model database service

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Key-value store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

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

firebase.google.com/products/realtime-database

azure.microsoft.com/services/cosmos-db

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

www.dragonflydb.io/docs

firebase.google.com/docs/database

learn.microsoft.com/azure/cosmos-db

Developer

DragonflyDB team and community contributors

Google

acquired by Google 2014

Microsoft

Initial release

2023

2012

2014

2009

Current release

1.0, March 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

hosted

Data scheme

scheme-free

schema-free

Typing

predefined data types such as float or date

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

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Android
iOS
JavaScript API
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

TinkerPop 3

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

Java
JavaScript
Objective-C

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Groovy
Java

Server-side scripts

Stored procedures

Lua

limited functionality with using 'rules'

JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

Callbacks are triggered when data changes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of command blocks and scripts

yes

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

Password-based authentication

yes, based on authentication and database rules

Access rights can be defined down to the item level

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