DBMS > Firebird vs. Google BigQuery vs. ObjectBox vs. PouchDB vs. Trafodion

System Properties Comparison Firebird vs. Google BigQuery vs. ObjectBox vs. PouchDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Large scale data warehouse service with append-only tables

Extremely fast embedded database for small devices, IoT and Mobile

JavaScript DBMS with an API inspired by CouchDB

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

www.firebirdsql.org

cloud.google.com/bigquery

objectbox.io

pouchdb.com

trafodion.apache.org

Technical documentation

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

docs.objectbox.io

pouchdb.com/guides

trafodion.apache.org/documentation.html

Developer

Firebird Foundation

Google

ObjectBox Limited

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2000

As fork of Borland's InterBase

2010

2017

2012

2014

Current release

5.0.0, January 2024

7.1.1, June 2019

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Initial Developer's Public License

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

JavaScript

C++, Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Android
iOS
Linux
macOS
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux

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

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

JavaScript

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

PSQL

user defined functions

in JavaScript

View functions in JavaScript

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

online/offline synchronization between client and server

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

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 IndexedDB, WebSQL or LevelDB as backend

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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