DBMS > Amazon DynamoDB vs. Firebase Realtime Database vs. IBM Db2 vs. JaguarDB vs. Quasardb

System Properties Comparison Amazon DynamoDB vs. Firebase Realtime Database vs. IBM Db2 vs. JaguarDB vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

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

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Performant, highly scalable DBMS for AI and IoT applications

Distributed, high-performance timeseries database

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Key-value store
Vector DBMS

Time Series DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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	13.64
Rank	#39	Overall
	#6	Document stores

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/dynamodb

firebase.google.com/products/realtime-database

www.ibm.com/products/db2

www.jaguardb.com

quasar.ai

Technical documentation

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/database

www.ibm.com/docs/en/db2

www.jaguardb.com/support.html

doc.quasar.ai/master

Developer

Amazon

Google

acquired by Google 2014

IBM

DataJaguar, Inc.

quasardb

Initial release

2012

1983

host version

2015

2009

Current release

12.1, October 2016

3.3 July 2023

3.14.1, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free version is available

Open Source

GPL V3.0

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

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

APIs and other access methods

RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Multi-source replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Immediate Consistency

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

rights management via user accounts

Cryptographically strong user authentication and audit trail

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