DBMS > Amazon Aurora vs. Dragonfly vs. EXASOL vs. Firebase Realtime Database vs. Snowflake

System Properties Comparison Amazon Aurora vs. Dragonfly vs. EXASOL vs. Firebase Realtime Database vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Document store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

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

www.exasol.com

firebase.google.com/products/realtime-database

www.snowflake.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

www.dragonflydb.io/docs

www.exasol.com/resources

firebase.google.com/docs/database

docs.snowflake.net/manuals/index.html

Developer

Amazon

DragonflyDB team and community contributors

Exasol

Google

acquired by Google 2014

Snowflake Computing Inc.

Initial release

2015

2023

2000

2012

2014

Current release

1.0, March 2023

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux

hosted

Data scheme

yes

scheme-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protocol

.Net
JDBC
ODBC
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
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

Java
Lua
Python
R

Java
JavaScript
Objective-C

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Lua

user defined functions

limited functionality with using 'rules'

user defined functions

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Callbacks are triggered when data changes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

ACID

yes

ACID

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

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

yes, based on authentication and database rules

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.