DBMS > Google Cloud Firestore vs. H2GIS vs. MySQL vs. Rockset vs. Trafodion

System Properties Comparison Google Cloud Firestore vs. H2GIS vs. MySQL vs. Rockset vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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.

Spatial extension of H2

Widely used open source RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Spatial DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

firebase.google.com/products/firestore

Technical documentation

firebase.google.com/docs/firestore

www.h2gis.org/docs/home

dev.mysql.com/doc

docs.rockset.com

trafodion.apache.org/documentation.html

Developer

Google

CNRS

Oracle

since 2010, originally MySQL AB, then Sun

Rockset

Apache Software Foundation, originally developed by HP

Initial release

2017

2013

1995

2019

2014

Current release

8.4.0, April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

Read-only SQL queries, including JOINs

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

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

Java

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

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

based on H2

yes

proprietary syntax

Java Stored Procedures

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

based on H2

Multi-source replication
Source-replica replication

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

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

yes

based on H2

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

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