DBMS > Bangdb vs. Firebird vs. Hive

System Properties Comparison Bangdb vs. Firebird vs. Hive

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

bangdb.com

www.firebirdsql.org

hive.apache.org

Technical documentation

docs.bangdb.com

www.firebirdsql.org/en/reference-manuals

cwiki.apache.org/confluence/display/Hive/Home

Developer

Sachin Sinha, BangDB

Firebird Foundation

Apache Software Foundation

initially developed by Facebook

Initial release

2012

2000

As fork of Borland's InterBase

2012

Current release

BangDB 2.0, October 2021

5.0.0, January 2024

3.1.3, April 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Initial Developer's Public License

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C and C++

Java

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like DML and DDL statements

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
Thrift

Supported programming languages

C
C#
C++
Java
Python

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

Server-side scripts

Stored procedures

PSQL

yes

user defined functions and integration of map-reduce

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

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

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Users with fine-grained authorization concept

Access rights for users, groups and roles

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More resources

DB-Engines blog posts

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