DBMS > Firebird vs. Google BigQuery vs. ObjectBox vs. Trafodion vs. Warp 10

System Properties Comparison Firebird vs. Google BigQuery vs. ObjectBox vs. Trafodion vs. Warp 10

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

Transactional SQL-on-Hadoop DBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Time Series DBMS

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

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

www.firebirdsql.org

cloud.google.com/bigquery

objectbox.io

trafodion.apache.org

www.warp10.io

Technical documentation

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

docs.objectbox.io

trafodion.apache.org/documentation.html

www.warp10.io/content/02_Getting_started

Developer

Firebird Foundation

Google

ObjectBox Limited

Apache Software Foundation, originally developed by HP

SenX

Initial release

2000

As fork of Borland's InterBase

2010

2017

2014

2015

Current release

5.0.0, January 2024

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

Open Source

Apache License 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++

C++, Java

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

Linux

Linux
OS X
Windows

Data scheme

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

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

Proprietary native API

ADO.NET
JDBC
ODBC

HTTP API
Jupyter
WebSocket

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

PSQL

user defined functions

in JavaScript

Java Stored Procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

online/offline synchronization between client and server

yes, via HBase

selectable replication factor

based on 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

based on HBase

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

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

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