DBMS > Google Cloud Firestore vs. openGauss vs. OpenQM vs. Quasardb vs. VoltDB

System Properties Comparison Google Cloud Firestore vs. openGauss vs. OpenQM vs. Quasardb vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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.

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

QpenQM is a high-performance, self-tuning, multi-value DBMS

Distributed, high-performance timeseries database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

firebase.google.com/products/firestore

gitee.com/opengauss
opengauss.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

quasar.ai

www.voltdb.com

Technical documentation

firebase.google.com/docs/firestore

docs.opengauss.org/en
gitee.com/opengauss/docs

doc.quasar.ai/master

docs.voltdb.com

Developer

Google

Huawei and openGauss community

Rocket Software, originally Martin Phillips

quasardb

VoltDB Inc.

Initial release

2017

2019

1993

2009

2010

Current release

3.0, March 2022

3.4-12

3.14.1, January 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++

Java, C++

Server operating systems

hosted

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

BSD
Linux
OS X
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

ANSI SQL 2011

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

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

JDBC
ODBC

HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
C++
Java

.Net
Basic
C
Java
Objective C
PHP
Python

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Java

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

yes

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using LevelDB

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

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

Access rights for users, groups and roles according to SQL-standard

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

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

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