DBMS > Firebird vs. HBase vs. Oracle Berkeley DB vs. Riak KV

System Properties Comparison Firebird vs. HBase vs. Oracle Berkeley DB vs. Riak KV

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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 in-process key-value store

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.firebirdsql.org

hbase.apache.org

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

www.firebirdsql.org/en/reference-manuals

hbase.apache.org/book.html

docs.oracle.com/cd/E17076_05/html/index.html

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Firebird Foundation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

originally developed by Sleepycat, which was acquired by Oracle

OpenSource, formerly Basho Technologies

Initial release

2000

As fork of Borland's InterBase

2008

1994

2009

Current release

5.0.0, January 2024

2.3.4, January 2021

18.1.40, May 2020

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache version 2

Open Source

commercial license available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

C, Java, C++ (depending on the Berkeley DB edition)

Erlang

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
Unix
Windows

using Cygwin

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

Data scheme

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

only with the Berkeley DB XML edition

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Java API
RESTful HTTP API
Thrift

HTTP API
Native Erlang Interface

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

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

PSQL

yes

Coprocessors in Java

Erlang

Triggers

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

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

yes, using Riak Security

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