DBMS > Amazon Redshift vs. BigObject vs. Dgraph vs. Firebird

System Properties Comparison Amazon Redshift vs. BigObject vs. Dgraph vs. Firebird

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Distributed and scalable native Graph DBMS

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Graph DBMS

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Website

aws.amazon.com/redshift

bigobject.io

dgraph.io

www.firebirdsql.org

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

dgraph.io/docs

www.firebirdsql.org/en/reference-manuals

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Dgraph Labs, Inc.

Firebird Foundation

Initial release

2012

2015

2016

2000

As fork of Borland's InterBase

Current release

5.0.0, January 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Initial Developer's Public License

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++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Synchronous replication via Raft

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

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

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

fine grained access rights according to SQL-standard

Planned for future releases

Users with fine-grained authorization concept

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