DBMS > Amazon DynamoDB vs. Firebird vs. MySQL vs. Trafodion

System Properties Comparison Amazon DynamoDB vs. Firebird vs. MySQL vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Firebird is an open source RDBMS forked from Borland's InterBase

Widely used open source RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	21.06
Rank	#31	Overall
	#19	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Website

aws.amazon.com/dynamodb

www.firebirdsql.org

www.mysql.com

trafodion.apache.org

Technical documentation

docs.aws.amazon.com/dynamodb

www.firebirdsql.org/en/reference-manuals

dev.mysql.com/doc

trafodion.apache.org/documentation.html

Developer

Amazon

Firebird Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation, originally developed by HP

Initial release

2012

2000

As fork of Borland's InterBase

1995

2014

Current release

5.0.0, January 2024

8.3.0, January 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Initial Developer's Public License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++, Java

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

PSQL

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

table locks or row locks depending on storage engine

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)

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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