DBMS > Amazon DynamoDB vs. BigchainDB vs. Brytlyt vs. Cubrid vs. Firebase Realtime Database

System Properties Comparison Amazon DynamoDB vs. BigchainDB vs. Brytlyt vs. Cubrid vs. Firebase Realtime Database

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Document store

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Website

aws.amazon.com/dynamodb

www.bigchaindb.com

brytlyt.io

cubrid.com (korean)
cubrid.org (english)

firebase.google.com/products/realtime-database

Technical documentation

docs.aws.amazon.com/dynamodb

bigchaindb.readthedocs.io/en/latest

docs.brytlyt.io

cubrid.org/manuals

firebase.google.com/docs/database

Developer

Amazon

Brytlyt

CUBRID Corporation, CUBRID Foundation

Google

acquired by Google 2014

Initial release

2012

2016

2008

2012

Current release

5.0, August 2023

11.0, January 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL v3

commercial

Open Source

Apache Version 2.0

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

Python

C, C++ and CUDA

C, C++, Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

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

ADO.NET
JDBC
ODBC
OLE DB

Android
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java Stored Procedures

limited functionality with using 'rules'

Triggers

yes

by integration with AWS Lambda

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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