DBMS > Amazon DynamoDB vs. Citus vs. FileMaker vs. Firebird vs. Galaxybase

System Properties Comparison Amazon DynamoDB vs. Citus vs. FileMaker vs. Firebird vs. Galaxybase

Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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

Scalable, ACID-compliant native distributed parallel graph platform

Primary database model

Document store
Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store

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	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Website

aws.amazon.com/dynamodb

www.citusdata.com

www.claris.com/filemaker

www.firebirdsql.org

galaxybase.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.citusdata.com

www.claris.com/resources/documentation

www.firebirdsql.org/en/reference-manuals

Developer

Amazon

Claris

a subsidiary of Apple

Firebird Foundation

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Initial release

2012

2010

1983

2000

As fork of Borland's InterBase

2017

Current release

8.1, December 2018

19.4.1, November 2021

5.0.0, January 2024

Nov 20, November 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL, commercial license also available

commercial

Open Source

Initial Developer's Public License

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 and C++

C and Java

Server operating systems

hosted

Linux

iOS

client part only
Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Data scheme

schema-free

yes

Strong typed schema

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

yes

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

via plugins

yes

APIs and other access methods

RESTful HTTP API

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

Filemaker WebDirect
JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

PHP

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Go
Java
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

PSQL

user defined procedures and functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication, warm standby

since Version 14

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

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Concurrency

Support for concurrent manipulation of data

yes

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

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

simple rights management via user accounts and connection to external directory services

Users with fine-grained authorization concept

Role-based access control

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