DBMS > Amazon DynamoDB vs. Brytlyt vs. Firebase Realtime Database vs. IBM Db2 vs. jBASE

System Properties Comparison Amazon DynamoDB vs. Brytlyt vs. Firebase Realtime Database vs. IBM Db2 vs. jBASE

Editorial information provided by DB-Engines

Name

Description

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

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

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

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

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

Multivalue 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	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

aws.amazon.com/dynamodb

brytlyt.io

firebase.google.com/products/realtime-database

www.ibm.com/products/db2

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

docs.aws.amazon.com/dynamodb

docs.brytlyt.io

firebase.google.com/docs/database

www.ibm.com/docs/en/db2

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Amazon

Brytlyt

Google

acquired by Google 2014

IBM

Rocket Software (formerly Zumasys)

Initial release

2012

2016

2012

1983

host version

1991

Current release

5.0, August 2023

12.1, October 2016

5.7

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free version is available

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, C++ and CUDA

C and C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

APIs and other access methods

RESTful HTTP API

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

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java
JavaScript
Objective-C

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

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

limited functionality with using 'rules'

yes

Triggers

yes

by integration with AWS Lambda

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

with separate tools (MQ, InfoSphere)

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

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

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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