DBMS > Google Cloud Firestore vs. Microsoft Access vs. Oracle vs. SQLite

System Properties Comparison Google Cloud Firestore vs. Microsoft Access vs. Oracle vs. SQLite

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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.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

firebase.google.com/products/firestore

www.microsoft.com/en-us/microsoft-365/access

www.oracle.com/database

www.sqlite.org

Technical documentation

firebase.google.com/docs/firestore

developer.microsoft.com/en-us/access

docs.oracle.com/en/database

www.sqlite.org/docs.html

Developer

Google

Microsoft

Oracle

Dwayne Richard Hipp

Initial release

2017

1992

1980

2000

Current release

1902 (16.0.11328.20222), March 2019

23c, September 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

Open Source

Public Domain

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++

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

server-less

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

but not compliant to any SQL standard

yes

with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

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

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

since Access 2010 using the ACE-engine

PL/SQL

also stored procedures in Java possible

Triggers

yes, with Cloud Functions

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

can be realized in PL/SQL

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

yes

ACID

but no files for transaction logging

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

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.

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard

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