DBMS > Drizzle vs. Firebird vs. Google Cloud Bigtable vs. Hawkular Metrics

System Properties Comparison Drizzle vs. Firebird vs. Google Cloud Bigtable vs. Hawkular Metrics

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

Key-value store
Wide column store

Time Series DBMS

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

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Website

www.firebirdsql.org

cloud.google.com/bigtable

www.hawkular.org

Technical documentation

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigtable/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Drizzle project, originally started by Brian Aker

Firebird Foundation

Google

Community supported by Red Hat

Initial release

2008

2000

As fork of Borland's InterBase

2015

2014

Current release

7.2.4, September 2012

5.0.1, August 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Initial Developer's Public License

commercial

Open Source

Apache 2.0

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++

C and C++

Java

Server operating systems

FreeBSD
Linux
OS X

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

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

with proprietary extensions

yes

APIs and other access methods

JDBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

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

HTTP REST

Supported programming languages

C
C++
Java
PHP

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

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

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

PSQL

Triggers

hooks for callbacks inside the server can be used.

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

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

selectable replication factor

based on Cassandra

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)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users with fine-grained authorization concept

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

Firebird – Director, Data Science (US)
26 September 2024, Music Business Worldwide

12 Top Open Source Databases to Consider
1 May 2024, TechTarget

Acosta Sales & Marketing Acquires Firebird Foods
7 September 2024, Supermarket News

Coachella Valley Firebirds @ Hershey Bears Friday, June 14, 2024 | TheAHL.com
13 June 2024, American Hockey League

DoNot Team's New Firebird Backdoor Hits Pakistan and Afghanistan
23 October 2023, The Hacker News

provided by Google News

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

Google introduces Bigtable SQL access and Spanner's new AI-ready features
1 August 2024, ZDNet

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

Google Cloud Adds GenAI, Core Enhancements Across Data Platform
1 August 2024, The New Stack

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News

Share this page