DBMS > Amazon DynamoDB vs. Citus vs. Datomic vs. Firebird vs. Infobright

System Properties Comparison Amazon DynamoDB vs. Citus vs. Datomic vs. Firebird vs. Infobright

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Document store
Key-value store

Relational 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Website

aws.amazon.com/dynamodb

www.citusdata.com

www.datomic.com

www.firebirdsql.org

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.citusdata.com

docs.datomic.com

www.firebirdsql.org/en/reference-manuals

Developer

Amazon

Cognitect

Firebird Foundation

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2012

2010

2012

2000

As fork of Borland's InterBase

2005

Current release

8.1, December 2018

1.0.6735, June 2023

5.0.0, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL, commercial license also available

commercial

limited edition free

Open Source

Initial Developer's Public License

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Java, Clojure

C and C++

Server operating systems

hosted

Linux

All OS with a Java VM

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
Windows

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

standard, with numerous extensions

yes

APIs and other access methods

RESTful HTTP API

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

RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
JDBC
ODBC

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

Clojure
Java

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

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

yes

Transaction Functions

PSQL

Triggers

yes

by integration with AWS Lambda

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

none

But extensive use of caching in the application peers

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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