DBMS > Drizzle vs. GBase vs. Google Cloud Firestore vs. Tkrzw

System Properties Comparison Drizzle vs. GBase vs. Google Cloud Firestore vs. Tkrzw

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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.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Document store

Key-value store

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.gbase.cn

firebase.google.com/products/firestore

dbmx.net/tkrzw

Technical documentation

firebase.google.com/docs/firestore

Developer

Drizzle project, originally started by Brian Aker

General Data Technology Co., Ltd.

Google

Mikio Hirabayashi

Initial release

2008

2004

2017

2020

Current release

7.2.4, September 2012

GBase 8a, GBase 8s, GBase 8c

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 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, Java, Python

C++

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

Linux
macOS

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

Standard with numerous extensions

APIs and other access methods

JDBC

ADO.NET
C API
JDBC
ODBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

hooks for callbacks inside the server can be used.

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

using specific database classes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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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

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Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

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

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News

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