DBMS > Blueflood vs. Firebase Realtime Database vs. Firebird vs. TerarkDB

System Properties Comparison Blueflood vs. Firebase Realtime Database vs. Firebird vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

blueflood.io

firebase.google.com/products/realtime-database

www.firebirdsql.org

github.com/bytedance/terarkdb

Technical documentation

github.com/rax-maas/blueflood/wiki

firebase.google.com/docs/database

www.firebirdsql.org/en/reference-manuals

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Rackspace

Google

acquired by Google 2014

Firebird Foundation

ByteDance, originally Terark

Initial release

2013

2012

2000

As fork of Borland's InterBase

2016

Current release

5.0.0, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Initial Developer's Public License

commercial

restricted open source version available

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

C and C++

C++

Server operating systems

Linux
OS X

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

predefined scheme

schema-free

yes

schema-free

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

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

C++ API
Java API

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

PSQL

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

yes, based on authentication and database rules

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

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