DBMS > Firebird vs. Google Cloud Bigtable vs. H2 vs. JaguarDB vs. Snowflake

System Properties Comparison Firebird vs. Google Cloud Bigtable vs. H2 vs. JaguarDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Performant, highly scalable DBMS for AI and IoT applications

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.firebirdsql.org

cloud.google.com/bigtable

www.h2database.com

www.jaguardb.com

www.snowflake.com

Technical documentation

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigtable/docs

www.h2database.com/html/main.html

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

Developer

Firebird Foundation

Google

Thomas Mueller

DataJaguar, Inc.

Snowflake Computing Inc.

Initial release

2000

As fork of Borland's InterBase

2015

2005

2015

2014

Current release

5.0.0, January 2024

2.2.220, July 2023

3.3 July 2023

License

Commercial or Open Source

Open Source

Initial Developer's Public License

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL V3.0

commercial

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

C and C++

Java

C++

the server part. Clients available in other languages

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

All OS with a Java VM

Linux

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PSQL

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

yes

yes, multi-version concurrency control (MVCC)

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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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