DBMS > Dolt vs. Drizzle vs. Google Cloud Firestore vs. Ultipa

System Properties Comparison Dolt vs. Drizzle vs. Google Cloud Firestore vs. Ultipa

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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

A MySQL compatible DBMS with Git-like versioning of data and schema

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

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.

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

Document store

Graph DBMS

Secondary database models

Document store

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

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

github.com/dolthub/dolt
www.dolthub.com

firebase.google.com/products/firestore

www.ultipa.com

Technical documentation

docs.dolthub.com

firebase.google.com/docs/firestore

www.ultipa.com/document

Developer

DoltHub Inc

Drizzle project, originally started by Brian Aker

Google

Ultipa

Initial release

2018

2008

2017

2019

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

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++

Server operating systems

Linux
macOS
Windows

FreeBSD
Linux
OS X

hosted

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

APIs and other access methods

CLI Client
HTTP REST

JDBC

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

RESTful HTTP API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java
PHP

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

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

Server-side scripts

Stored procedures

yes

currently in alpha release

yes, Firebase Rules & Cloud Functions

Triggers

yes

hooks for callbacks inside the server can be used.

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication
Source-replica replication

Multi-source replication

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

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

Dolt- A Version Controlled Database
29 January 2024, iProgrammer

Top Data Version Control Tools for Machine Learning Research in 2023
24 July 2023, MarkTechPost

Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

Radar Trends to Watch: July 2022 – O'Reilly
5 July 2022, O'Reilly Media

provided by Google 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

Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available
8 February 2019, InfoQ.com

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Ultipa Secures New Real-time Graph Database Deals with Central Banks and Regulators
25 March 2024, Headlines of Today

provided by Google News

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