DBMS > Firebird vs. HBase vs. PostgreSQL vs. Quasardb

System Properties Comparison Firebird vs. HBase vs. PostgreSQL vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Wide column store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

Technical documentation

www.firebirdsql.org/en/reference-manuals

hbase.apache.org/book.html

www.postgresql.org/docs

doc.quasar.ai/master

Developer

Firebird Foundation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

PostgreSQL Global Development Group

www.postgresql.org/developer

quasardb

Initial release

2000

As fork of Borland's InterBase

2008

1989

1989: Postgres, 1996: PostgreSQL

2009

Current release

5.0.0, January 2024

2.3.4, January 2021

16.3, May 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache version 2

Open Source

BSD

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C and C++

Java

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
Unix
Windows

using Cygwin

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like query language

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Java API
RESTful HTTP API
Thrift

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

HTTP API

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

PSQL

yes

Coprocessors in Java

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Users with fine-grained authorization concept

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

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